BPM Skills in 2026 – Hot or Not
Blog: BPM Tips
It’s time for a new post from the BPM Skills series with many thought-provoking answers from BPM experts (and not only)!
What to expect in 2026? Many companies are investing heavily in AI. New models are becoming increasingly powerful and are outperforming humans on many benchmarks. AI can be used to build agents and power humanoid robots, which could dramatically change how work is done.
On the other hand, not all AI initiatives have been successful (to put it mildly). Add to this changes in global supply chains and greater unpredictability in the business environment, and it feels like “interesting times,” to borrow the phrase.
How will these changes affect the role of BPM, and what do BPM practitioners need to do to stay relevant?
Check out the thought-provoking answers for the usual set of questions from 20+ BPM experts plus few extras: answers from a perspective of a Business Analyst and advice for organization leaders.
As always, you can either read everything or use the navigation below. Enjoy!
Wil van der Aalst
Tony Benedict
Lloyd Dugan
Scott Francis
Ian Gotts
Paul Holmes-Higgin and Joram Barrez
Caspar Jans
Mathias Kirchmer
Mirko Kloppenburg
Harald Kühn
Amy Van Looy
Madison Lundquist
Jan Mendling
Nathaniel Palmer
Brian Reale
Adrian Reed
Björn Richerzhagen
Pedro Robledo
Michael Rosemann
Serge Schiltz
Jim Sinur
Roger Tregear
Roland Woldt
Which BPM skills will be hot in 2026
Now, let’s dive into the answers.
Prof. Wil van der Aalst
Prof.dr.ir. Wil van der Aalst is a full professor at RWTH Aachen University, leading the Process and Data Science (PADS) group. He is also the Chief Scientist at Celonis and part-time affiliated with the Fraunhofer FIT. Currently, he is also deputy CEO of the Internet of Production (IoP) Cluster of Excellence and co-director of the RWTH Center for Artificial Intelligence. His research interests include process mining, data science, process intelligence, business process management, workflow automation, Petri nets, process modeling, and simulation. Many of his papers are highly cited (he is one of the most-cited computer scientists in the world and has an H-index of 188 according to Google Scholar with over 169,000 citations), and his ideas have influenced researchers, software developers, and standardization committees working on process support. According to Research.com, he is the highest-ranked computer scientist in Germany and ranked 8th worldwide (ranking 2025). He previously served on the advisory boards of several organizations, including Fluxicon, Celonis, ProcessGold/UiPath, and aiConomix/Automaited. Van der Aalst received honorary degrees from the Moscow Higher School of Economics (Prof. h.c.), Tsinghua University, and Hasselt University (Dr. h.c.). He is also an IFIP Fellow, IEEE Fellow, ACM Fellow, and an elected member of the Royal Netherlands Academy of Arts and Sciences, the Royal Holland Society of Sciences and Humanities, the Academy of Europe, the North Rhine-Westphalian Academy of Sciences, Humanities and the Arts, and the German Academy of Science and Engineering. In 2018, he was awarded an Alexander-von-Humboldt Professorship.
WWW: http://www.vdaalst.com
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Twitter: @wvdaalst
How do AI and other trends impact the way organizations manage and run their processes?
AI is dramatically accelerating digital work, but it also exposes a long-standing weakness: organizations often lack a reliable, real-time understanding of how their processes actually function.
Generative, predictive, and prescriptive AI bring powerful capabilities, but only if they are connected to operational reality. AI needs process context, structured event data, and end-to-end visibility. Without these, AI will make processes faster, but not necessarily better. We risk accelerating inefficiencies, fragmenting responsibilities, or automating tasks that shouldn’t exist in the first place.
The most important shift is conceptual: moving from reactive process management, focused on dashboards and after-the-fact reports, to proactive and even autonomous operational steering. This shift requires:
- object-centric event data covering many interconnected processes,
- continuous monitoring rather than one-time analysis
- AI assistance that works on process models (not only text), and
- automated predictions and recommendations grounded in data semantics.
When processes become digitally transparent across objects, systems, and departments, AI can be used responsibly to suggest interventions, prevent bottlenecks, and optimize operations holistically. But if AI is used locally, optimizing individual tasks or documents in isolation, it can inflate work, obscure structures, and overwhelm people.
Ultimately, the organizations that will benefit from AI are those that combine automation with process awareness and operational grounding.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
A practitioner in 2026 will require a combination of process expertise, data fluency, and responsible AI thinking. The following dimensions will matter most:
Skills and techniques
- working with object-centric event data and multi-object process views
- process-aware predictive and prescriptive analytics
- data extraction, transformation, and semantic modeling
- real-time monitoring and operational process control
- integrating AI/LLM components into structured process contexts
- reference model use and domain-specific process standardization
- optimization, simulation, and scenario evaluation
Behaviors and attitudes
- evidence-based reasoning rooted in actual event traces
- critical assessment of automation proposals
- resistance to local sub-optimization
- interdisciplinary communication skills (IT, business, data science)
- comfort with hybrid intelligence – orchestrating humans + AI systems
- attention to unintended process consequences
The practitioner needs curiosity, scepticism toward purely technical promises, and confidence in working with high-dimensional process data across systems.
What are the best resources to learn those skills? (e.g. books, articles, courses)
I’m currently working on a new version of the process mining book. This will appear in 2026 (published again by Springer).
Moreover, I recommend reflecting on our recent BISE editorial “Process Mindlessness: When we Lose Sight of What AI is Supposed to Improve”. Bus Inf Syst Eng 67, 771–775 (2025). https://doi.org/10.1007/s12599-025-00972-0. Here, we discuss three potential problems that arise when applying AI naively. When applied without process awareness, AI may unintentionally worsen operational processes rather than improve them. Three effects illustrate how the misuse of AI can undermine process performance and transparency.
A short summary:
1. Bloating: inflating process artifacts rather than streamlining work.
Generative AI makes it effortless to produce text, reports, tickets, emails, and documentation. Instead of clarifying process steps, AI can flood a process with additional artifacts, status updates, autogenerated logs, long explanations, masking the true flow of work. The result is process noise: more events and documents without added value.2. Blurring: dissolving precise process information into ambiguous text.
Organizations maintain structured data representing objects, lifecycle transitions, and constraints. When AI converts such structured information into free-form text to generate recommendations or actions, semantics are blurred. Decision logic becomes implicit and probabilistic rather than explicit and verifiable. Blurring erodes the “single source of truth” required for process intelligence.3. Blasting: scaling local automation without process constraints.
AI systems can act rapidly and at scale, generating messages, tasks, or transactions far faster than human agents. When such actions are not governed by process models, workloads shift downstream, overwhelming teams and breaking throughput assumptions. Traditional capacity constraints, once natural brakes, vanish, and without monitoring, the process destabilizes.
Which skills are no longer relevant or not practically applicable yet (hype)?
Some established skills are losing relevance, and some emerging skills are still hyped because they lack grounding in operational reality.
Declining relevance
- ability to generate text, reports, and PowerPoint presentations,
- case-centric process thinking as the dominant process lens,
- manual KPI dashboarding detached from the underlying event data,
- modeling-first approaches without factual logs, and
- single-task automation without systemic process awareness.
Not practically applicable yet or overhyped
- autonomous AI process agents without human oversight or auditability,
- workflows delegated entirely to generative models without grounding,
- AI that converts structured process data into text only to re-interpret that text,
- unbounded automation that scales communications and actions without constraints, and
- simplistic claims that AI eliminates the need for process understanding.
These trends tend to ignore unintended consequences such as bloating, blurring of semantics, and blasting effects that overload process participants.
AI offers unprecedented opportunities for process excellence, but only when it is grounded in factual event data, connected across objects, and aligned with process goals. The skills that matter are those that combine process science, data science, and responsible automation, while guarding against naive forms of AI adoption that accelerate fragmentation rather than improvement. If you automate nonsense, you just get automated nonsense (faster).
Tony Benedict
Tony Benedict is a Partner with Omicron Partners, LLC, a strategy advisory firm. He is a senior level operations executive best known for transforming organizations, improving operational excellence and profitability. Most recently, he served as Interim Vice President of Operations for Rising Pharma, managing all phases of complex $200M post-merger integration of 2 acquired companies (36 CMOs, 2 3PLs) within expedited timeframe, while concurrently launching a state-of-the-art pharma distribution center. Consolidated 3 ERP systems into a single SAP instance within 6 months. Benedict previously worked at HonorHealth as Vice President, Procurement and Supply Chain where he was responsible for over $600M in spend management. One of his accomplishments was in the restructuring of the procurement and supply chain organizations post-merger within 12 months and consolidating two ERP systems within 18 months while implementing $60M in cost reduction initiatives. Previously, he was Chief Information Officer, Vice President of Supply Chain for Tenet, and Vice President, Supply Chain, Vanguard Health Systems at Abrazo Community Health Network in Arizona.
He is currently serving as President and Director, Board of Directors for the Association of Business Process Management Professionals International and is a co-author of the Business Process Management Common Body of Knowledge versions 2, 3 and the recently released version 4.
WWW: http://www.abpmp.org
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How do AI and other trends impact the way organizations manage and run their processes?
The failure rate for AI projects to date has been over 70%. Companies have learned that injecting a new technology into your business shouldn’t be the primary strategy, rather that AI should augment business strategy. The challenge will be for more selectivity and prioritization for where the investments in AI should be made. The larger the company, especially multi-nationals, the more complexity, making AI models larger and implementations extremely difficult. I believe that successful companies will start where they have thoroughly documented their processes. The logical areas would be customer and supplier facing processes with customer facing taking priority given the impact on revenue. Companies can achieve quick wins within these two areas while they concurrently work on the major cross functional processes that touch the customers and suppliers to fully streamline and optimize internal operational efficiency.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
Building algorithms and language models will largely be left to technical analysts and developer types who are working on smaller scope projects. There is a tremendous need for a Business Architect Strategist to oversee enterprise level transformational efforts. The competency and skills required for practitioners will focus on greater depth and breath of business architecture strategy, integration and governance. The full list of competency areas are Strategy, Operations, Enterprise Performance Management, Human Dynamics, Enterprise Modeling, and Enterprise Governance inclusive of all the skills within each competency area. A complete competency matrix will be available at TheEssentialBusinessArchitect.org or at ABPMP.org
What are the best resources to learn those skills? (e.g. books, articles, courses)
The BPM CBOK is a good start for those Director level practitioners who want the foundation for BPM. The best training is “on-the-job” training where the practitioner actually learns by doing. Every transformation is different and the diversity of experience will be the best teacher. Make every effort to increase the depth and breadth of your project experience while increasing scope to the enterprise level. If you do the same project work and the same scope then you’re not growing as you should in this profession. Find a very senior practitioner who can mentor you. Enterprise Governance will be more important now and in the future. Also, The Business Architect Consortium will be publishing “The Essential Skills of the Business Architect” in mid to late January 2026 which will outline what competencies and skills are needed for enterprise level transformation. Find our more at TheEssentialBusinessArchitect.org or at ABPMP.org
Which skills are no longer relevant or not practically applicable yet (hype)?
The BPM profession is not a “throw away” profession where certain skills are not longer relevant or applicable It’s always a question of what skills to use and why/when. As mentioned in the previous question, What is becoming more important is a greater depth and breadth of certain skills, many of which are non-technical and Business in nature. Competencies like strategy, systems thinking, operational integration, governance, etc.
Lloyd Dugan
Lloyd Dugan is a widely recognized thought leader in the development and use of leading modeling languages, methodologies, and tools, covering from the level of EA and BA down through BPM, Case Management, and SOA. He specializes in the use of standard languages for describing business processes, systems, and services, particularly BPMN, CMMN, and DMN from the OMG. He has developed and delivered BPMN 2.0 training to the U.S. Department of Defense and large consultancies. He has nearly 40 years of experience with public and private sector clients, and has an MBA from the Fuqua School of Business at Duke University. He is a past member of the Workflow Management Coalition and its BPSim Working Group that produced the process simulation standard, and also a past member of the OMG’s BPMN Model Interchange Working Group (MIWG). He is a Contributing Member (author) and Collaboration Team Member for the BA Meta Modeling and BPM-BA Alignment Groups of the Business Architecture Guild. He represents the Guild on the OMG Task Force for the BA Core Metamodel (BACM) standard. He is a frequent speaker at national and international conferences on BPM, BPMN, Case Management, Decision Management, SOA, and BA. He is a published author or co-author on BPM, BPMN, and BA. He led the effort to develop a new OMG certification for integrating BPMN, DMN, and CMMN, known as BPM+. He serves as the Chief Architect for Serco, NA, on its CMS Eligibility Support Program, which provides back-office processing of applications to access the Federal Health Care Exchange created under the Affordable Care Act, and where he has led award-winning efforts to build intelligent document processing, dynamic work assignment queuing, RPA for case management, use of AI/ML, process mining, and migration of all Program elements to the AWS Cloud. He still delivers BPM-related training, and when asked also provides client advisory services on BPM-related matters/technologies.
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How do AI and other trends impact the way organizations manage and run their processes?
It is truly swimming against the tide when it comes to attempting to convince folks to NOT think about AI as anything other than a monolithic black box straight out of “2001: A Space Odyssey”. In other words, there is not a simple, one-size-fits-all answer to this question, but rather specific answers that support distinct and identifiable use cases.
For example, AI technologies and the models that power them are now sufficiently capable of doing time-saving and productivity-enhancing activities for the analyst such that one can vibe-review/engineer models and code constructs, create documentation and design artifacts, summarize findings, etc. via well-targeted prompting. This saves on the effort to do the leg-work previously needed, but I think this is first-cut stuff that still warrants a practiced eye’s review…at least for a while longer. However, this says only so much about using such things as part of business process automation.
Regarding those use cases, AI technologies and the models that power them are increasingly capable of automating the execution of more complex tasks with more reliability, such that human-in-the-loop (HITL) is becoming more of a bug than a feature. New design patterns have emerged, such as Agentic AI, where the probabilistic logic of AI and deterministic decision logic combine into adaptive behavior by systems. The advent of retrieval-augmented generation (RAG)-based systems is making for more domain-specific results with less likelihood of hallucination, and now with the underlying knowledge bases of the business better understood and implemented. This helps the business to decide between pre-trained and to-be-trained models for risk/reward payoff.
Some use cases have always been there, but AI now provides stronger and more available tools to address them. An example of this is fraud detection, which is not a new need but is now better enabled via the latest AI. Of course, this is all part of the escalation where AI feeds both fraudsters and fraud-detectors in a never-ending race.
As with any impactful IT, all of this needs to be under some kind of governance, and there is substantial literature out there on this topic. As usual, the US is lagging behind Europe in tackling this because of pervasive and misguided laissez-faire takes on how best to advance the development of AI. It is not rocket science nor regulatory overreach to apply common sense requirements to the use of AI. It is simply sound thinking.
So, in conclusion, AI is part of the IT stack, fitting in where it can provide the best value. Sounds like any other IT that’s come along over the years. And like any other IT, we must come to terms with its use, and align management practices accordingly.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
The usual things are still true – namely: operational modeling and simulation, process and data analysis, an abiding intellectual curiosity about how to improve how things work, etc. – but the value gap between what the experienced practitioner can provide vs. what the noobie can provide is continuing to shrink as generative AI tools mature. However, greater reliance on such tools comes at the cost of losing the deep understanding that powers the discipline of BPM, widening the divide between those that simply produce artifacts for base level consumption by others and those that produce constructs that are intended to execute in production as automated processes.
One way to navigate the tensions created between these two Scylla-and-Charybdis forces is to be able to exploit domain-specific knowledge and to professionalize the deep understanding of BPM as a discipline – at least as long as there is value-add to practical experiences over AI “smarts”. The deep understanding needed is built around operational modeling, such as with BPM+ (BPMN/DMN/CMMN) and Value Stream Modeling (Value-generation), and knowing how best to capture the behaviors of AI in such models, making its role explicit rather than tacit. For example, work out how best to represent AI-enabled moments in an operational model that support automation without confusing (too much) business stakeholders. This can be done and taught.
Better understanding of the domain can come through use of knowledge graphs about the business, which AI and associated models should be built around. This should all be seen as just another thing about AI that BPM practitioners can get smarter about.
What are the best resources to learn those skills? (e.g. books, articles, courses)
I have found this book a great primer for AI/ML, but there are plenty of books to read: https://www.barnesandnoble.com/w/knowledge-graphs-mayank-kejriwal/1137268183.
I have found this book to be a great primer on governance, but other books exist: https://www.amazon.com/AI-Algorithms-Mastering-Ethical-Compliance/dp/1634624564.
For operational modeling with BPMN, there is an abundance of options available that a simple Internet search will reveal (including one for the author of this very website). Fewer, if just focused on DMN, but that continues to be a hot one, so also too many to cite. Few for CMMN, but I still have hopes that that turns around. BPM+ is about the unification/integration across all three, and there are some options, and even an integrative exam that I and others helped craft. Advanced Value Stream Modeling remains criminally underserved, but I’m hoping to turn that around in the future too.
Regarding AI/ML, there is all sorts of material out there. AWS, whose Bedrock set of services present a strong foundation (but not for the noobies) in AI/ML, has a set of training options, and given the cloud vendors investment here should be considered: https://aws.amazon.com/ai/learn/.
For a more contextual and philosophical take, I’ll plug something from an early source of BPM inspiration for me, Tom Koulopoulos, that he recently started (though I have yet to take) and a book from him and my long-time friend, mentor, boss, and collaborator Nathaniel Palmer: The Future of AI: Humanity’s Next Frontier and https://www.amazon.com/Gigatrends-Forces-Changing-Future-Billions/dp/1637589808.
Which skills are no longer relevant or not practically applicable yet (hype)?
AI is rendering the background technical architecture for accessing data and application logic increasingly like a utility that one knows is there but doesn’t have to know too much about to use – think about how you don’t need to understand too much about electricity to use it in one’s household. As an example of this, note that one of the things that BPM technologies still have a lot to say about is service orchestration, but model context protocol (MCP) is moving to claim that space.
Deep technical knowledge may be receding in importance, but deep understanding of how things work remains key. I hope that strong – and especially domain-specific – understanding of how things work and can be improved for processes remains just as vital as it has for decades. I see in this a parallel with data science, which is more about understanding the meaning of data and the patterns therein than about where it resides and how to access it.
Scott Francis
Scott Francis is President of Westslope Advisors, providing advisory and board services to growing and scaling firms and sharing what he’s learned from 30 years in Technology. Scott formerly led BP3 Global, Inc, and held senior roles at Lombardi Software and Trilogy Software. You can find his writings on Substack and Medium.
WWW: https://sfrancisatx.substack.com/
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How do AI and other trends impact the way organizations manage and run their processes?
A major impact of AI has been to slow budget spend on everything that isn’t “AI”. I highly recommend rebranding and reframing your process work as critical AI work. Organizations that try to manage and run their processes with AI today will have serious issues with hallucinations and inconsistencies, which are unacceptable for businesses. We do not expect calculators to be right 85% of the time. They are right 100% of the time, or we don’t use them. Generative AI asks us to lower our standards for what constitutes successful automation – but that error rate will lead to either bad business outcomes, or inordinate spending on “fixing” the AI results. Neither is acceptable.
What does work, is letting your processes manage AI. You use AI in the context of a business process with all of its inputs, outputs, and process flow context. You put AI algorithms into processes the same way. This gives you the scaffolding to make AI a productive and useful part of the systems that participate in your processes. AI is not a substitute for understanding your business processes and operational processes. AI is not a substitute for designing them, though you may well consult with AI tools on how to design them, and how to improve them.
Harking back to BPM the third wave: first, there’s the process instance and how you execute it (think, a single order). Second, there’s another dimension that is the collection of all the process instances of that process, and how they are managed collectively (think, all orders being processed). Third, there’s the dimension that is evaluating and improving the process definition for the future, based on what you are learning from the work that is happening now and in the past. AI can play a role in each.
In the first, it is subsidiary to the process instance and should be controlled by the process definition. In the second, AI can help identify problematic instances (orders for example), or highlight trends, or offer advice in response to queries from a manager for example, with respect to load management or likely risk. In the third, AI can provide advice on improving the process definition for the future based on past results.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
The traditional skills, techniques, behaviors and attitudes will continue to provide value in 2026. In fact, if you exhibit those values, you may find yourself an increasingly rare commodity. My advice is to continue to focus on designing for humans in the business – AI and process, when done right, greatly improve the human experience and customer experience in a business.
Another skill that is incredibly important in today’s world: the ability to estimate when an AI-focused project or program will complete. As an industry, many tech executives and IT executives have lost the ability to estimate when AI is involved, because it doesn’t follow the old rules for estimation in software. I’ wrote a whole post about this here: https://sfrancisatx.substack.com/p/we-are-terrible-at-estimating-progress Because I think this is a real challenge to many companies and executives, I recommend really working on how to estimate and when a good estimate is not possible. It’s a long read, but hopefully worth it.
What are the best resources to learn those skills? (e.g. books, articles, courses)
I can recommend two great resources:
1. Enterprise Process Orchestration – this is the book I wish I had written, and that I would recommend to every single BPM practitioner, and every single person who cares about process orchestration. https://www.amazon.com/Enterprise-Process-Orchestration-Hands-Technology/dp/1394309678 – by Berndt Rücker and Leon Strauch.2. Irresistible Change, by Phil Gilbert https://www.amazon.com/Irresistible-Change-Blueprint-Buy-Breakout/dp/1394367759/. One of the main reasons we do this work is because we are effecting change within large organizations with complex processes. Phil gives here the how-to on making change – at scale – irresistible. It’s an amazing read.
Which skills are no longer relevant or not practically applicable yet (hype)?
Vibe coding. You can vibe code one-off utilities and single use programs. But if you vibe code ATM Clearing transactions, bad things will happen. This doesn’t mean you shouldn’t use AI assistants for coding, validating code, understanding code. But don’t confuse vibe coding with professional software development, with production use in mind.
Ian Gotts
Ian Gotts. Speaker : Analyst : Advisor
WWW: https://iangotts.medium.com
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Business Analysis 2026: Why Domain Expertise is Your New Superpower
TL;DR
By 2026, we’ll have crossed the Carbon-Silicon Divide and the Business Analyst role will have bifurcated. Artificial Intelligence will automate the “mechanics” of analysis—mapping, documentation, and basic requirements gathering. This leaves the human BA with a binary choice: become a deep domain expert who directs the AI, or face irrelevance.
The rise of “vibe coding” and autonomous agents means building solutions is faster than ever. But speed without direction is just chaos accelerated. The future belongs to those who can provide the precise context, nuance, and industry expertise that AI lacks. That is the critical thinking that great Business Analysts provide, in teh context of the deep domain expertise.
Crossing the Carbon-Silicon Divide
For over two decades, the holy grail of Business Analysis was to capture a process and have the application generate automatically. We tried utilizing standards like UML and BPMN, but they largely failed for one reason: we were forced to describe business in terms computers understood—”silicon”. To make the logic executable, the resulting diagrams had to be so dense, rigid, and complex that often only their creators could decipher them .
AI has finally shattered that barrier. We no longer need to learn the syntax of the machine; the machine has learned ours. We can now describe business needs in natural language—”carbon”—and trust the AI to handle the translation into code and logic. As noted in my Forbes article “Silicon Vs. Carbon: Finally, Computers Are Speaking Our Language“, this doesn’t absolve us of critical thinking; much like delegating to a skilled intern, we must still be specific and clear about what we want. But the friction is gone. We have finally crossed the carbon-silicon divide, moving from a world where we serve the syntax to one where the syntax serves us.
The “Vibe Coding” Trap
We are entering the era of “vibe coding,” where anyone with an idea can describe it in natural language, and an AI will generate the code. While many current examples are prototypes, the trajectory is undeniable. The barrier to building software is collapsing.
However, the determining factor in the quality of these apps is no longer coding skill—it is the quality of the description. In the old world, a human developer might push back if a specification didn’t make sense or lacked organizational context. An AI vibe coding platform will not. It will build exactly what you asked for, errors and all.
This shines a harsh spotlight on the quality of Business Analysis.
- The stakes are higher: If you describe a flawed process, you get a flawed app instantly.
- Requirements are critical: You must “bottom out” the specification. What are the specific business processes? What is the data model?
- Architecture matters: If the app is destined for production, who is considering scaling, maintenance, and compliance?
As application generation becomes effortless, the rigor of the analysis becomes the only safety net.
Programming with English: The Rise of Agents
We are already managing a digital workforce. At Elements.cloud, we have deployed agents to support teams in every department. They have employee records, formal onboarding, and scheduled reviews. They aren’t replacing people; they are liberating them.
Take “Fin,” our support agent. Fin is now answering 90% of inbound customer questions accurately. For the 10% it cannot answer, it passes them to a human support team with a full analysis already complete. Furthermore, our internal “case to bug” agent has reduced resolution time from 23 days to 5, increasing documentation quality from 0.8/10 to 9/10.
But here is the catch: Agents are literal. An agent has limited common sense and zero organizational intuition. It will read a 200-page policy document in seconds and execute instructions precisely. If those instructions (your business processes) are loose, ambiguous, or rely on “tribal knowledge,” the agent will fail .
The ability to “agentify” an organization relies entirely on the quality of your process documentation .
- Process as Code: You are essentially programming with natural language .
- The Detail Gap: Humans cover up gaps in bad processes with workarounds. Agents do not.
- Documentation: If your agents are unreliable, it is almost always a failure of business analysis, not the technology.
The Death of the Generalist
We have built a Business Analysis (BA) Agent. It is impressive. It can interview stakeholders, identify missing steps, suggest improvements, and draw the process diagram automatically . It leverages the collective knowledge of Large Language Models (LLMs) which have “read” about every industry on earth.
So, what is the future of the human Business Analyst if an agent can do the heavy lifting in a week?
The answer is deep domain expertise.
The “A” in AI stands for Augment. A BA Agent is only as good as the context it is fed. If you ask it to define a field service process for upstream oil and gas, it will give you a technically correct, generic answer. But it won’t know the specific compliance nuances of your geography, your company’s specific operating model, or the political landscape of your stakeholders.
- The Generalist’s Risk: If you are a generalist BA who simply transcribes what people tell you into diagrams, you are at risk. An agent can do that faster and cheaper. When asked your ara of expertise, it cannot be “Oil and Gas”. THat is too broad. “Downstream Oil and Gas” whilst narrower is again is huge domain. “Filed Service for downstream Oil and Gas” is a tighter area, but still has a huge scope.
- The Expert’s Opportunity: If you are a domain expert, AI makes you the smartest person in the room. You can use the agent to handle the drudgery—drafting, mapping, checking for consistency—allowing you to focus on high-value strategy and complex problem solving. So take time to assess your experience to pinpoint your area of expertise and work out how to deepen that.
Paul Holmes-Higgin
Dr Paul Holmes-Higgin, Fellow and co-founder of Flowable. Previously, as co-founder and CPO of Alfresco. Paul brought Activiti to the fore of the company’s innovation. A long-time Open Source advocate, he believes it has an important role to play in making today’s innovation more widely available. His PhD and background in AI gives him a deep understanding of the opportunities and realities of Machine Learning. Paul sees innovation around the standard models of BPM as the best way to bring together his passions for human-centred software and intelligent automation in today’s highly dynamic business and social environment.
WWW: https://flowable.com
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Joram Barrez
Joram Barrez is a Business Process Management and open-source expert, working as a principal software architect at Flowable. With over fifteen years of real-world BPM experience, Joram is known for his contributions to the field, constantly pushing the boundaries of innovation and efficiency. He’s one of the founders of the Flowable open-source project and Activiti before that, and has worked on JBoss jBPM early on in his career. Throughout the years, Joram has worked with numerous global companies, helping them optimize their processes and drive digital transformation.
WWW: https://flowable.com
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How do AI and other trends impact the way organizations manage and run their processes?
[PHH] Are there any other trends apart from generative AI? I think the “introducing AI with guardrails” trend in BPM is now dated, but what modern BPMs have always been doing is showing up as things get real with AI. That is, managing business processes that interact with external services, mixed with human interaction; all auditable and secure.
The automation focus is now far more on declarative, agentic behavior, rather than procedural flows for business solutions.
[JB] Agreed. I’m a big believer of declarative approaches. Instead of trying to map every possible path upfront, we can now describe the problem and let an AI agent determine the steps to reach a solution. In enterprise settings, though, it only really works with strong governance in place: clear boundaries, auditability, and explicit rules around what an agent is allowed to decide on its own.
That’s why I see context engineering as the real differentiator going forward. In many ways, this is not new to BPM. We’ve been doing it for years through processes, and even more through case management. The goal has always been the same: make sure the right information reaches the right person or system at the right time. Each interaction adds context, which then drives the next action, whether human or automated.
[PHH] One other trend is the build v. buy software selection decision changing to AI code-generated prototype solutions, before even thinking about a vendor. Liberal open source BPMs (Apache, MIT-licensed etc) are freely available libraries for AIs to exploit, but they can grow into full-strength enterprise platform use once the business solution has been proven.
[JB] Another way to look at this is to ask a simple question: what are the foundational building blocks for the next generation of intelligent automation? For me, processes, cases, workflows or whatever you name it (and the APIs that expose and interact with them) sit right at the center. They provide the structure AI agents need to operate effectively and safely inside an enterprise.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
[JB] Building on what I just said, declarative thinking will only become more important. At the same time, the fundamental skills that have always defined BPM practitioners remain crucial, arguably more so than ever. Making sure solutions meet data security standards, governance policies, and regulatory requirements is non-negotiable today. And with new players entering the field, that challenge is only getting tougher.
[PHH] I really think we should change the mindset, so that BPM means Business Problem Management, to avoid the easy oversimplification that everything is a sequential, procedural process. A business process is about getting an outcome from an initial situation. What happens in between is a blend of machine and human intelligence with repeatable best practice.
What are the best resources to learn those skills? (e.g. books, articles, courses)
[PHH] Get your hands dirty and try things out, because the technology is moving too fast for books or courses – even an online resource will be out of date at depth. Download the open source or trial versions of BPM platforms and use AI-generated BPM standard models to see how agentic solutions can work today. To learn CMMN through a book, Bruce Silver’s “CMMN Method and Style” is your best option.
[JB] Absolutely. We’re very much in an experimentation phase. Best practices are evolving so rapidly that what we write today can become outdated tomorrow. As you say, the most effective way to stay ahead is by actively experimenting with the capabilities and understanding what works in practice. On that note, I couldn’t agree more about CMMN: the evaluation-cycle approach in “case” management fits perfectly with agentic ways of working. It’s a natural match: structured flexibility that balances control with flexibility.
Which skills are no longer relevant or not practically applicable yet (hype)?
[JB] One side-effect of generative AI is that people are reading less, relying on AI to summarize and extract key information quickly. When I started in BPM a long time ago, a big part of my work was process discovery: interviewing stakeholders, summarizing their intents, finding gaps to automate and sketching back-of-the-napkin diagrams. The essence of that work won’t disappear, but with today’s tools, how that information is gathered and processed is changing very fast.
Similarly, some technical skills are becoming less central. Early in my career, we crafted XML by hand; later, visual modeling made syntax less of a worry. Today, we can interact with models directly, applying changes or querying them via AI, without knowing every detail. The focus is shifting from mastering mechanics to orchestrating strategically and understanding how models drive real outcomes.
[PHH] Just don’t expect AI-generated BPM models to be production ready! I could be controversial and say not to spend time on RPA if you aren’t already committed to it: AI-generated code will do the same.
Caspar Jans
Caspar is a seasoned BPM professional with 25 years of experience in various industries. From managing a center of excellence on BPM for a global manufacturing company, hosting a podcast on BPM and consulting large enterprises on the benefits of a process centric approach to being a Principal BPM Expert for Celonis, Caspar has been on both sides of the table on process management (and more). On top of that, Caspar is listed in the PEX Network Global Top 25 though leaders on Operational Excellence.
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How do AI and other trends impact the way organizations manage and run their processes?
With the introduction of AI also came the realization that your business processes actually provide the necessary alignment and guard rails for AI to be successful within. Without this, AI tends to spin out of control. The developments on the AI front are going so fast that the usual governance concepts can’t keep up and in order to offset that, a proper process landscape (connected to roles, applications, input/outputs and more) is vital. So, there seems to be a revived interest in how to efficiently and effectively document processes, not just for the sake of documenting them, but for the sake of being able to also orchestrate and automate them (either via automation platforms or AI).
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
The BPM practitioner has to become much more allround compared to the last decade. Just being knowledgeable on how to model and govern processes will simply not be sufficient anymore. BPM practitioners will need at least basic understanding on topics like orchestration, automation, AI and maybe even the most important one: human psychology, because after all, if you want to implement successful change within an organization, you will have influence people rather than software or hardware. Being an avid communicator will help the BPM practitioner to more eloquently explain why having a governed and up to date process landscape is vital for all of the AI use cases.
What are the best resources to learn those skills? (e.g. books, articles, courses)
For the more general background on BPM I would suggest the youtube channel of Roger Tregear (the Australian BPM guru) or season 1 of the BPM360 podcast (explaining the 4 key success criteria for BPM implementations in great detail). Also the book on “influence” by Robert Cialdini is a recommendable book (for the human behavioral part).
Which skills are no longer relevant or not practically applicable yet (hype)?
Given the emergence of AI assistants in BPM, the modeling skill has become less relevant (in terms of: you don’t need that many modelers anymore and their work emphasis changes a bit from creating to validating process documentation). The model to execute skill (so the ability to model a process and then ingest it straight into an execution engine) is emerging but not yet critical to master for now.
Dr. Mathias Kirchmer
Dr. Kirchmer is an experienced practitioner and thought leader in the field of Business Process Management (BPM) and Digital Transformation. He is Managing Director of Scheer Americas, previously BPM-D US. He co-founded BPM-D, a consulting company focusing on performance improvements and appropriate digitalization by establishing and applying the discipline of BPM. Before he was Managing Director and Global Lead of BPM at Accenture, and CEO of the Americas and Japan of IDS Scheer, known for its process modelling software and process consulting.
Dr. Kirchmer has led numerous transformation and process improvement initiatives in various industries at clients around the world. He has published 11 books and over 150 articles. At the University of Pennsylvania and at Widener University he has served as affiliated faculty for over 20 years. He received a research and teaching fellowship from the Japan Society for the Promotion of Science.
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WWW:https://www.scheer-americas.com/
Twitter: @mtki2006
How do AI and other trends impact the way organizations manage and run their processes?
Business Process Management (BPM) has become the management discipline that moves strategy into people and technology-based execution, fast and reliably. It creates the transparency necessary to take fast well-informed decisions and implement the related actions effectively. This transparency is the foundation of success in the digital age. The discipline of BPM helps to align business and technology aspects towards the goals of an organization to create the expected value.
Most process improvement initiatives must leverage digital technologies to achieve the desired agility, flexibility, innovation and efficiency. Realizing the business potential of those digital technologies has become a key role of BPM, delivering process-led digital transformation. This includes the identification of the improvement opportunities through AI. The visibility BPM provides helps to identify systematically where AI helps to enhance the end-to-end performance of business processes.
With Agentic AI, the role of BPM continues to evolve. Intelligent agents create process instances more and more independently, with little to no human intervention. Therefore, BPM shifts its focus from the design of operational processes to defining their deliverables and performance levels. Related data requirements are crucial and need to be addressed through the BPM-Discipline. Governance and management process become increasingly more significant.
BPM provides the “process of process management” integrating and aligning process, data and AI governance to provide the necessary control and rapid adjustment of the highly automated business processes. BPM moves from addressing mainly the design and implementation of operational processes to delivering appropriate management and governance processes.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
BPM Practitioners need to focus increasingly on delivering process-led digital transformation through appropriate standardization, optimization and innovation of processes. They organize the required management and governance processes, integrating process, data and AI requirements through the definition of a company specific “process of process management”, realizing value and driving the ongoing transformation journey. Therefore, BPM Practitioners need to understand both the business aspects of processes and the effects of digital technologies that support these processes. BPM Practitioners need to know how to create and apply related assets, such as software-based process reference models.
Process standardization remains an important topic since it simplifies digital transformation and makes it more efficient. BPM Practitioners need to develop related skills, such as the definition of the right degree of abstraction and detail for a specific standardization initiative or the appropriate leverage of process reference models.
Not all processes are equal. BPM Practitioners need to identify the 10-15% high impact processes for sophisticated innovation and optimization initiatives. Commodity processes are improved by applying industry common practices to reach an average performance level. Sophisticated optimization doesn’t pay off here. BPM Practitioners need to be able to apply process impact and maturity assessments to achieve the required process segmentation.
The role in digital transformation requires the handling of related data aspects. Developing logical data models and simplifying those to enable nimble processes as well as supporting applications becomes an important skill. The design of appropriate data management processes becomes another important task.
The high degree of automation allows the collection of related data. This enables the use of “digital twins” to manage processes more effectively. BPM Practitioners help to develop and apply those digital twins.
The BPM-Discipline goes through a digital transformation itself. The integrated use of BPM tools, such as modelling, mining and automation tools, leveraging AI, becomes an important success factor. BPM Practitioners need to drive this transformation of BPM.
What are the best resources to learn those skills? (e.g. books, articles, courses)
Specialized consulting and education organizations offer training and eLearning addressing those skills, such as Scheer with its academy and publications (www.scheer-americas.com). Industry organizations, like APQC (www.apqc.org), ABPMP (www.abpmp.org) or the BPM Institute (www.bpminstitute.org), provide related resources. Forward thinking universities and research organizations address related topics, for example the August-Wilhelm Scheer Institute for Digital Processes and Products (www.aws-institut.de), the Scheer School for Digital Sciences (Scheer School of Digital Sciences – Saarbrücken – Scheer School of Digital Sciences at Saarland University), Widener University with its master program for Digital Transformation (www.widener.edu) or the University of Pennsylvania (www.upenn.edu).
Here are some related readings that may help:
• Scheer, A.-W.: Digitale Industrie: Daten – Prozesse – Metaverse. New York, Berlin, e.a. 2025 (English version to follow in 2026).
• Scheer, A.-W.: The Composable Enterprise: Agile, Flexible and Innovative – A Gamechanger for Organizations, Digitalization and Business Software. 4th ed., New York, Berlin, e.a. 2023.
• Kirchmer, M., Havaligi, S.: Realizing the full Potential of AI Applications through Business Process Management. In: Shishkov B. (ed): Business Modeling and Software Design. BMSD 2025. Lecture Notes in Business Information Processing, vol 559 (ISBN: 978-3-031-98032-9). Springer, 2025.
• Kirchmer, M.: Process-led Digital Transformation – Mastering the Journey towards the Composable Enterprise. In: Shishkov B. (ed): Business Modeling and Software Design. BMSD 2024. Lecture Notes in Business Information Processing, vol 523 (ISBN: 978-3-031-64072-8). Springer, 2024.
• Wilson, H.J, Daugherty, P.R.: Generative AI – The Secret to Successful AI-driven Process Redesign. In: Harvard Business Review, January-February 2025.
• Kirchmer, M.: High Performance through Business Process Management – Strategy Execution in a Digital World. 3rd ed., New York, Berlin, e.a. 2017.
• Franz, P., Kirchmer, M.: Value-driven Business Process Management – The Value-Switch for Lasting Competitive Advantage. New York, 2012.
Which skills are no longer relevant or not practically applicable yet (hype)?
Traditional improvement approaches that do not address the alignment of business and information technology or do not leverage digital technologies as appropriate to enhance processes will no longer be successful. Every transformation is related to some degree of digital transformation.
General principles of process improvement as applied in approaches like Lean, Six Sigma or Kaizen remain true and useful. But to stay relevant they must be upgraded, leveraging modern digital process management capabilities, such as mining or modelling tools.
Mirko Kloppenburg
Hi, I’m Mirko. I’m living in Hamburg, Germany, with my wife and our two daughters. For more than 20 years, I’ve been working in Business Process Management – starting in large, complex organizations and today helping companies build truly process-driven organizations.
I’m creator of the New Process approach and founder of NewProcessLab.com, where I combine BPM, New Work, and experience design into a human-centric approach to process management. My focus is on BPM as a leadership and management capability: creating clarity, enabling people, and turning strategy into action through processes.
I host the New Process Podcast, where I share real-world BPM experiences, frameworks, and conversations with practitioners from around the world.
WWW: NewProcessLab.com
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Twitter: @MirkoKBurg
How do AI and other trends impact the way organizations manage and run their processes?
AI is fundamentally changing how work is executed – but not why work exists.
In many organizations, AI is currently introduced as a technology initiative. New models, agents, and tools promise efficiency and autonomy. At the same time, we see many AI initiatives struggling or failing because underlying processes are unclear, fragmented, or not owned by anyone.
This is where BPM becomes more important than ever.
In an increasingly unpredictable environment – with volatile supply chains, geopolitical shifts, and rapid technological change – organizations need orientation, clarity, and adaptability. BPM provides exactly that by making value creation explicit end-to-end, clarifying responsibilities, and creating a shared understanding of how work actually gets done.
AI will automate decisions, generate content, and execute tasks. But BPM must ensure that:
– processes are meaningful and aligned with strategy,
– humans remain accountable for outcomes,
– and AI is embedded intentionally into workflows, not layered on top of confusion.I see BPM evolving from a discipline focused on optimization to a management capability that enables learning, resilience, and informed decision-making in an AI-enabled world.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
To stay relevant in 2026, BPM practitioners must shift from being process experts to becoming process enablers and sense-makers.
From my perspective, four capability areas matter most:
1. Strategic positioning of BPM: BPM practitioners must be able to connect purpose, strategy, and processes. This includes articulating why BPM matters, what impact it creates, and how it contributes to business strategy in times of uncertainty.
2. Implementing pragmatic BPM frameworks: Instead of heavyweight governance, organizations need lightweight, usable BPM frameworks that provide orientation without bureaucracy. This includes clear process architectures, meaningful communication, and well-defined roles such as Process Owners as real leadership roles.
3. Enabling people, not controlling them: The ability to inspire people for processes, facilitate dialogue, and build a process culture is becoming a core skill. BPM only creates value if people understand, accept, and actively shape their processes.
4. Applying AI with intention: BPM practitioners don’t need to become AI engineers. But they must understand where deterministic automation, GenAI, AI agents, or human decision-making are appropriate – and where they are not. The key skill is judgment, not tool mastery.
Underlying all of this is a mindset shift: from “designing processes” to continuously enabling organizations to learn and adapt through processes.
What are the best resources to learn those skills? (e.g. books, articles, courses)
I believe BPM skills are best developed where practice, reflection, and exchange come together.
Peer communities and practitioner exchange are extremely valuable, because they surface real-world challenges and patterns beyond theory. For example, New Process Pro is a free community where BPM practitioners share experiences, discuss frameworks, and reflect on what it really takes to build process-driven organizations.
Structured learning formats can help to create orientation, especially for practitioners who want to position BPM more strategically. A good starting point is a concise BPM roadmap that connects strategy, processes, and people – before diving into methods or tools.
Curated content such as podcasts, blogs, and BPM platforms helps to stay connected to the broader BPM discourse and emerging perspectives.
Most importantly, learning happens through application: facilitating workshops, coaching Process Owners, experimenting with BPM frameworks, and reflecting on what actually creates impact in a specific organizational context.
Examples mentioned above:
New Process Pro Community: https://www.newprocesslab.com/pro
BPM Roadmap Mini Course: https://www.newprocesslab.com/roadmap
Which skills are no longer relevant or not practically applicable yet (hype)?
No BPM skill is irrelevant per se – relevance always depends on purpose and context.
That said, I currently see a strong overemphasis on tools and technology compared to foundational capabilities.
Highly detailed process modeling, tool-driven BPM initiatives, or AI-first approaches often create activity without impact when organizations lack clarity about:
– their end-to-end processes,
– process responsibilities,
– and purpose.Similarly, fully autonomous, self-optimizing process visions are still largely aspirational for most organizations. Without a strong process culture and clear accountability, they remain more hype than reality.
What is often underestimated – and still underdeveloped – are skills related to leadership, facilitation, sense-making, and cultural change. In 2026, these will differentiate BPM practitioners far more than technical specialization.
Harald Kühn
Dr. Harald Kühn is a member of the management board of the BOC AG. He is responsible for the product management and the related strategic aspects of BOC’s ADONIS and ADOIT product portfolio. Dr. Harald Kühn works in the areas of BPM, EA, their integration and the usage of innovative technologies in these domains.
He is an author of over 20 publications about various aspects of BPM.
WWW: boc-group.com
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Twitter: @BOC_Group
How do AI and other trends impact the way organizations manage and run their processes?
If you provide this question to the ChatBots of the big players (see question 3), you already get very good answers with various perspectives on the related impact. No need to repeat the answers here.
Independent of that, I personally see three concrete impacts:
- In the near future, human work processes will be primarily influenced by AI-based technology for “knowledge-related tasks” (white-collar tasks) such as writing, analyzing, summarizing, researching, planning, programming, testing, conceptualizing, managing etc. For the next 3-5 years I do not see a major impact on “manual tasks” (blue-collar tasks) of human work processes such as repairing of physical things, construction, outdoor services, maintenance activities, nursing services etc. The latter might change with the upcoming wave of AI-based robotics.
- In the domain of “knowledge-related tasks” I see intensive usage of AI-based technology within all kind of tasks. This leads to a distinctive productivity boost for “knowledge-related tasks”, but not a complete replacement of such tasks by AI. As a result, the nature of human work will continuously change from “do-ing” to “govern-ing”.
- In the domain of “machine-based processes” or “automated processes” I see a clear trend to extend the automation domain from pre-defined or rule-based execution to agentic execution. The domain of agentic AI is still in an early maturity level, but the evolution speed rapidly accelerates (https://aaif.io/).
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
To be honest, actually I do not see big differences between 2025 and 2026 on this topic. But it might be even more important to focus on speed to deliver value and results quickly as just having an eye on costs and short-term profitability.
- Continuous Learning: As the work environment, used technologies, practices, methodologies etc. are continuously changing, the learning process must do so as well. Continuous learning involves the persistent broadening of knowledge and abilities. Within the realm of workplace professional development, it focuses on acquiring new competencies and insights, as well as reinforcing previously acquired skills and knowledge.
- Practical Engagement with AI-based Tools: To successfully integrate AI with its different flavors such as Machine Learning, GenAI, Agentic AI etc. into BPM, practitioners in 2026 must prioritize continuous learning. This includes formal training, up-to-date online courses, and participation in global industry events tailored to AI advancements. Hands-on experience remains vital – through pilot projects, close collaboration with technology teams, and practical applications such as designing contextualized prompts or applying domain-specific models. Particular emphasis should be placed on addressing modern challenges like information security, data privacy, and the ethical use of company data in conjunction with public GenAI and/or Agentic AI services. Furthermore, staying actively connected with the BPM and AI communities is critical. Engaging in professional forums, participating in discussions on cutting-edge case studies, and networking with experts will ensure practitioners remain informed about the latest trends, tools, and best practices shaping the field in 2026.
- Use of Conceptual Modelling: The intensified use of multi-perspective conceptual modeling continues, incorporating sustainability, customer journeys, digital ecosystems, and value streams into cohesive BPM methodologies. This is accompanied by using a mix of different design, analysis and data-science techniques.
What are the best resources to learn those skills? (e.g. books, articles, courses)
A very valuable resource is of course Zbigniew’s recent co-authored book
:
Practical Business Process Modeling and Analysis: Design and optimize business processes incrementally for AI transformation using BPMNIn general, I heavily recommend to use ChatBots as “interactive learning companions”. Especially if you use various of them in a combined way. They already reached a reasonable mature state including the possibility to guide you to trustful information sources during your “learning dialog” or to use their agentic features for powerful research. Very good examples are Le Chat by Mistral (https://chat.mistral.ai/chat), Gemini by Google (https://gemini.google.com/app), ChatGPT by OpenAI (https://chatgpt.com/), Copilot by Microsoft (https://copilot.microsoft.com/), Claude by Anthropic (https://www.anthropic.com/claude) or Perplexity AI (https://www.perplexity.ai/).
Books on Conceptual Modelling:
Domain-Specific Conceptual Modeling (Part 1): Concepts, Methods and Tools,Domain-Specific Conceptual Modeling (Part 2): Concepts, Methods and ADOxx Tools,
Domain-Specific Conceptual Modeling (Part 3): The OMiLAB Community of Practice,
Metamodeling: Applications and Trajectories to the Future.
Free Conceptual Modelling Tools:
Library of more than 80 OMiLAB Modelling Tools,
Which skills are no longer relevant or not practically applicable yet (hype)?
Any knowledge and experiences gathered in the past will influence decisions for the future. Therefore, even if specific skills, techniques or technologies are not really relevant any more, they are important to evaluate, decide on and apply new upcoming approaches.
Prof. dr. Amy Van Looy
Prof. dr. Amy Van Looy holds a Ph.D. in applied economics. Before entering academia, she worked as an IT consultant. Being an associate professor at Ghent University, she coordinates the research cluster of “Process orientation” at the Department of Business Informatics and Operations Management. She teaches, among others, courses on research methods, process management, technology innovation and social media. Amy Van Looy is the recipient of the “Highest Award for Achievement” at the Dale Carnegie Consulting Program in 2007, the “Award for Best Contribution” at the OnTheMove Academy in 2010, the faculty’s “PhD Tutor Award” in 2022, as well as paper nominations (e.g., BPM2018, HICSS2025) and paper rewards (e.g., BPM2019). She was nominated in the top-10 for “Young ICT Lady of the year 2014” by the Belgian magazine DataNews, and was recognized as a tech role model by the non-profit “InspiringFifty Belgium” in 2020 (i.e., for being one of Belgium’s 50 most inspiring women in technology).
WWW: https://www.amyvanlooy.eu/
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How do AI and other trends impact the way organizations manage and run their processes?
The biggest 2026 trend affecting how organizations are looking at their business processes is definitely related to generative artificial intelligence (genAI), including all its variants, tools, and (potential) realizations. It is true that AI in general has already been frequently mentioned in the past years as a dominant technology to support and rethink business processes (e.g., by software robots such as robotic process automation and chatbots as well by physical manufacturing robots and service robots). And this AI wave will continue to evolve, but now being specifically expanded with genAI.
Especially the rapid pace and new possibilities offered by genAI increasingly raise questions on how to properly take advantage of the wide range of more novel, widespread and accessible genAI opportunities. Of course, this also come with the need for a more critical attitude toward genAI use, which I still consider as a major challenge for organizations and society at large. For instance, genAI can be positively supporting routine tasks and beyond, while also security and ethical concerns need to be more carefully addressed. For instance, examples are related to underlying copyright issues and hallucination problems with fake information. Nevertheless, I am sure that 2026 will bring new avenues to further explore how genAI can be used for facilitating all kinds of BPM activities in a more trusted and fair manner, among others during process modelling, process execution and process optimization.
Additionally, instead of seeing genAI as taking over human tasks or human roles, a more strategic approach is required to use genAI for the better. By this, I mean using genAI for dealing with internal and external pressures that come, among others, from pressures surrounding burnouts, work overload problems, social and green sustainability, customer centricity, and agility needs. Besides strategic alignment for genAI, also business-IT alignment issues remain critical.
Hence, the AI trends in general and genAI in particular demonstrate once more that the BPM discipline is not just a technical discipline but also a true managerial discipline that needs a holistic lens by extending the traditional BPM lifecycle with managerial, cultural and structural features to obtain long-term process performance outcomes.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
Thinking in terms of end-to-end value streams (instead of ad-hoc projects or siloed functional views per department) will remain highly important in 2026. By this, I mean putting the end customers first, and then exploring what business opportunities appear based on using digital technologies. While customer thinking is not necessarily new to 2026 (also in earlier years), much stronger employee-related skills will be needed to explore such business process opportunities because this contrasts from incremental process changes. Instead, upgrading skills related to out-of-the-box thinking, co-creation, ecosystem thinking, and experimentation with trial-and-error will increase much more in importance for creating business value to organizations.
Also, this value thinking needs to be further extended beyond purely financial or economic value (e.g., not just in terms of process costs, time, quality, flexibility). Instead, value thinking also need reconsidering the ecological footprints of specific business processes and the related social implications for obtaining a more responsible way of applying BPM. In this regard, AI algorithms are not necessarily fair and could be biased towards certain majority views. Also in decision-making, AI decision support mechanisms are not necessarily transparent and genAI features still have a high risk of hallucinations and so providing fake information. Consequently, a critical eye on using BPM for the good, will only increase in importance in 2026. This applies to everyone involved in BPM, namely BPM users, analysts, developers and employees in general will substantially benefit from a more open though critical view on how to explore those technology-based process opportunities.
What are the best resources to learn those skills? (e.g. books, articles, courses)
Since genAI and other digital technologies are evolving, it remains important for organizations to stay up-to-date about recent developments in the digital landscape and which BPM implications are related. For instance, managers and employees can attend seminars, conferences and even look for collaborations with universities (e.g., for participating in case study research or action-based research). Managers can also inform themselves about BPM updates by talking to consultants, especially since their own company’s core competence might not necessarily be in BPM and digital technologies. This way of working also aligns with the idea of ecosystem thinking, namely partnering with other companies and universities to find synergies and co-creation options.
Furthermore, managers and employees might follow Master university classes (e.g., as a kind of credit contract system) on the advanced and/or emerging topics of BPM, process mining and process innovation. Just one example is a practitioner-oriented Springer handbook that explains how organizations can improve their business processes based on agile projects by taking advantage of digital technologies, and which is also used as university teaching materials with a lot of practical cases (https://link.springer.com/book/10.1007/978-3-031-59770-1).
Additionally, the annual International Business Process Management Conference will be organized in Toronto this year, and which I highly recommend for your October planning. This conference offers a broad range of workshops, fora, panels, presentations, etc. Such a conference is also a nice way for networking and getting in touch with BPM scholars and industry professionals.
Which skills are no longer relevant or not practically applicable yet (hype)?
The BPM skills of, let us say 20 or 30 years ago, are still relevant nowadays to exploit daily business. It is rather a matter of extending them with more explorative skills for also thinking in terms of innovating business processes in an agile manner. The underlying idea of process modelling, monitoring and optimization is still needed, and will remain valid. This means that the BPM lifecycle remains more or less the same, though requiring faster iterations in particular. While process execution used to be with software-specific BPM systems (or alternatively, ERP or SAP systems), those dedicated tools are now being extended towards more AI and genAI features by tool vendors. Hence, I consider those renewed skills and features not as opposing to or contradicting with conventional BPM skills, but rather as an organic evolution towards more ambidexterity for which the traditional exploitation of business processes remains valid while also keeping an eye on exploring new business opportunities and benefiting from digital technologies.
Madison Lundquist
As Principal Research Lead, Madison Lundquist develops and executes APQC’s research agenda for process and performance management and serves as subject matter expert. She interviews leading organizations on their practices, identifies key findings from the research projects, and shares the approaches and best practices organizations use to manage processes, improve organizational agility, and continuously improve.
WWW: apqc.org/expertise/process-performance-management
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How do AI and other trends impact the way organizations manage and run their processes?
While the digital landscape is evolving rapidly, I don’t believe the fundamentals of BPM are changing all that much. If anything, having a strong foundation is becoming even more critical. The core essentials of process management remain consistent. Each year, when we ask process professionals about their priorities and challenges, the same themes continue to surface: process management, continuous improvement, and data and measurement. New technologies like AI, automation, and process mining can be powerful enablers, but they don’t replace the basics. In the end, people still run processes, and people don’t naturally love change—strong change management is what helps organizations move forward.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
Each year, APQC surveys process professionals to understand their priorities and challenges for the year ahead. This year’s data highlights three areas where change is most needed within the process discipline: technology and tools, a more collaborative culture, and stronger integration with IT. In my view, these areas are deeply interconnected, especially as the digital landscape continues to evolve. Process professionals increasingly recognize the need to work more closely with IT to successfully implement new tools and technologies, and that level of integration isn’t possible without a collaborative culture.
When we look more closely at the skills BPM practitioners need to develop, survey participants consistently point to design thinking, change management, and analytics as the most critical. Together, these skills help practitioners not only design better processes but also drive adoption and demonstrate value through data.
What are the best resources to learn those skills? (e.g. books, articles, courses)
APQC has a robust Resource Library that includes content critical to process management professionals, along with our training courses and webinars that help process professionals learn the necessary skills to be successful in an ever-changing business environment.
Which skills are no longer relevant or not practically applicable yet (hype)?
Looking at our survey data over the past several years, problem solving and data management/data visualization have declined in perceived importance. We’re also seeing facilitation and project management ranking lower for 2026, which I find surprising. Facilitation, in particular, remains a critical skill for process professionals—especially when the goal is to truly understand how work happens across the organization. Strong facilitation and project management skills are what enable teams to thoughtfully assess the current state, propose meaningful improvements, and successfully execute change.
I also believe data management and visualization are undervalued in this year’s results. As digital tools and technologies evolve rapidly, clean, well-managed data becomes even more essential. Underestimating the importance of data foundations could ultimately create challenges for organizations that don’t invest the time and attention these skills require.
Prof. Dr. Jan Mendling
Prof. Dr. Jan Mendling is the Einstein-Professor for Process Science with the Department of Computer Science at Humboldt-Universität zu Berlin, adjunct professor at Wirtschaftsuniversität Wien, and Principal Investigator at the Weizenbaum Institute, Berlin. His research interests include various topics in the area of business process management and information systems. He is co-author of the textbooks Fundamentals of Business Process Management and Wirtschaftsinformatik. He has published more than 500 research papers and articles, among others in IEEE Transaction journals and MIS Quarterly. He is inaugural Co-Editor-in-Chief of Process Science and Co-Founder of Noreja, a tool vendor focusing on generative process intelligence.
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How do AI and other trends impact the way organizations manage and run their processes?
Best the organizational management of processes should dictate where which AI technology is used to make a substantial impact on the processes. But yes, AI functionality also improves and speeds up the way how we manage our processes. In noreja, we have integrated analytical support based on GenAI. Agentic functionality will be next. Autonomous agents will take care of tasks in the background and trigger actions where necessary.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
Companies need resilience more than ever. This requires building capabilities and having processes under control. The next crisis is just around the corner. Denial is the wrong response to it.
What are the best resources to learn those skills? (e.g. books, articles, courses)
The Fundaments of Business Process Management capture all the core methods that have not changed. It is great to see that now translations are available in German, French, Greek, Indonesian, Mongolian, Persian, Polish, Spanish, Ukrainian and soon also Brazilian Portuguese and Italian. These translations make fundamental BPM concepts even more accessible. I am very grateful for those who took part in the translation teams.
Which skills are no longer relevant or not practically applicable yet (hype)?
The Case Management Model and Notation is no more relevant. Among others, Camunda has marked their CMMN support as deprecated for a while. In contrast, agentic automation is on the rise in exactly this spot. Where CMMN was meant to address the underspecification of processes that humans should somehow fill, it is exactly here that agentic process automation can fill the gap.
Nathaniel Palmer
Nathaniel Palmer is the CEO of Infocap AI Corp and the author of “Gigatrends” (2024) which recently reached #1 on Amazon’s “Hot New Releases” list for books on AI and Machine Learning. Rated as the “#1 Most Influential Thought Leader in Business Process Management (BPM)” by independent research, Nathaniel has also co-author over a dozen books on BPM and Process Improvement, as well as being the first individual named as a “Laureate in Workflow.” Over his career has he has the led the design and execution for some of the industry’s largest and most complex projects involving investments exceeding $200 Million and has overseen more than $2.5 billion in R&D around automation and AI.
WWW: www.infocap.ai
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How do AI and other trends impact the way organizations manage and run their processes?
Finally (!!) we are witnessing the inescapable yet fundamental shift from process as a static artifact to living, adaptive system.
For decades BPM was defined by documenting workflows, standardizing execution, and incrementally improving efficiency. The notion of adaptable, dynamic defined processed emerged as a first-class citizen within the BPM discipline in the late-2000s with Adaptable and Dynamic Case Management. Yet until now it was cast within the false dichotomy of Adaptability versus Automation – rather than embracing and enabling Adaptable Automation.
Today AI (notably Agentic AI) turns that notion on its head. Unlike Generative AI tools that provide answers or generate content, the newest wave of AI can act by executing tasks, collaborating with humans, and dynamically adapting to new challenges. “Agentic” or “Agent AI” moves beyond providing information to taking action, enabling processes which are no longer simply executed, but interpreted, optimized, and acted upon dynamically by digital workers operating, either with agency (autonomously) or working in concert with humans co-workers.
This present three significant changes in perspective on how changing how organizations manage and run processes.
First, work is moving from information → action. Generative AI was interesting when it produced answers. It becomes transformational when it executes multi-step workflows autonomously. That turns processes into decision-driven systems, not flowcharts.
Second, organizations are shifting from task automation to end-to-end orchestration. Intelligent automation now spans documents, decisions, integrations, compliance, and human collaboration—collapsing silos that BPM unintentionally reinforced for decades.
Third, trust becomes the limiting factor. Black-box AI fails in regulated, mission-critical environments. The future belongs to glass-box automation: observable, explainable, auditable systems grounded in operational excellence disciplines, not statistical mysticism.
In short, AI doesn’t replace or obviate process management, but rather hastens its need for successful business transformations, especially where AI adoption is deemed a key success factor.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
Most of all (and building on the points above) the BPM practitioner of 2026 is no longer a process modeler but rather the designer of human-machine collaboration. This true not just for human facing processes, but in understanding and leading the holistic orchestration of processes (or more apropos, attempting to holistically understand the process and moments of automation within your enterprise).
The new mission of BPM practitioners is make palpable and comprehendible to business stakeholders the re-envisioning the structure of the task to be not a single, discrete unit of work, but business outcomes, and to remove the distinction between what supports a task and the task itself – as well as who performs the work.
This is framed by making the work done by humans more consistent, predictable, and less reliant upon subjective interpretation of policies and rules, while simultaneously expanding the aperture for what is automatable, where digital workers and human workers use the same systems, follow the same rules, as well as are equally observable and accountable. Success requires a new set of critical skills and techniques than previously defined BPM as a discipline. These include:
- Decision Intelligence & Rule Design: the ability to externalize decisions from code and models into explicit, governed logic is foundational. If you can’t explain why a system acted, you don’t control it.
- Agent Orchestration & Digital Workforce Design: practitioners must design how AI agents, humans, and systems collaborate—who decides, who executes, who escalates.
- Operational Data Literacy: not data science, but knowing which data matters operationally, how it flows, and how it creates accountability.
- Process Observability & Metrics: AI without measurement is theater, not transformation.
- BPMN as an AI Orchestration Language: there are very individuals sufficiently knowledgeable of BPMN, DMN, and CMMN to use create useful models of agentic workflows which stand on their own, yet BPMN remains the closest thing to a true lingua franca for AI Orchestration.
Behaviors and attitudes that create value
- Skeptical optimism: excited about AI, intolerant of hype.
- Human-centric mindset: automation exists to amplify human capability, not obscure responsibility.
- Systems thinking: understanding second- and third-order impacts of automation across people, compliance, and culture.
- Governance-first thinking: designing control, transparency, and auditability from day one.
The practitioners who thrive will be those who can translate ambition into execution, rather than evangelizing a particular methodology or technology. Be a change agent and transformer, not an ideologue.
What are the best resources to learn those skills? (e.g. books, articles, courses)
Books
- Gigatrends (Koulopoulos/Palmer, 2024): a foundational primer for understanding where work, identity, AI and automation are heading over the next decade and beyond.
- Decision Management Systems (Taylor/Raden) still one of the clearest foundations for understanding decision intelligence
- Business Process Management: A Rigorous Approach (Martyn A. Ould): still the single best source for understanding BPM as a discipline and as a learning foundation to build upon with contemporary concepts such as agentic AI.
Technical Learning Paths
- Python (if not already conversant, start your own learning path and explore frameworks such as Django, Flask, FastAPI, et al.)
- Decision intelligence and rules-based automation platforms
- Low-code / no-code workflow orchestration tools
- AI governance and compliance training (especially for regulated sectors)
The driving the learn path behind the modern BPM Practitioner should be learning how to operationalize AI, not how to demo it.
Which skills are no longer relevant or not practically applicable yet (hype)?
Some hard truths about skills that are no longer relevant or mostly hype:
- Pure process modeling without execution context: BPMN diagrams that never touch production systems are mostly irrelevant, and this is most of them (i.e., out of the sum total of process modeling artifacts only a small percent make it execution). Process modeling is not dwindling in value as much as it is becoming a lost art, but what will sustain it is the ability to create models as living artifacts, able to be linked to execution context.
- “Prompt engineering” as a standalone skill: useful tactically, but not a profession. Prompts don’t scale, but the key to success for a BPM Practitioner has always come down to the ability to ask the right questions. In the GenAI era this will often mean framing the right questions as prompts, but prompts are only as effective the questions they represent (however they are expressed).
- Black-box machine learning for core operations: if you can’t explain or audit it, you can’t deploy it responsibly at scale. All decisions and actions made through automation must be transparent, observable, and appealable.
- AI “ethics” without operational accountability: Ethical AI discussions disconnected from real workflows, controls, and metrics are well-intentioned but insufficient. Focusing on automated outcomes is more important than chasing model training bias.
- AI-powered Automation Without Modeling: The biggest hype of all is the belief that AI strategy can exist without operational excellence. It cannot. That gap is where most failures occur. Automating poorly designed processes is faster than process improvement, and can also be more effective when transparent and aligned to outcomes. The critical difference is not upfront re-engineering but continuous measurement and optimization.
AI doesn’t diminish the role of BPM. Raises it raises the bar and hastens the need for skill BPM professionals able to apply traditional methods to contemporary system design. The future belongs to practitioners who can design clarity in a world of increasing autonomy.
Brian Reale
Brian Reale is a serial entrepreneur. Brian founded a telecommunications company in 2000 called Unete Telecomunicaciones which provided, voice, data, and satellite services in Latin America. Brian sold Unete to a publicly traded US telecom company in 2000. Brian was also the co-founder of Spotless LLC, an entertainment technology company that developed projection mapping technology for major live entertainment industries.
Brian has been involved in the workflow and BPM industry since he co-founded ProcessMaker in 2000. ProcessMaker is a leading open source BPM suite. The ProcessMaker BPMS has been recognized with numerous awards and pushes the bounds of BPM with a fundamental belief that process management can be simple, elegant, and easy to use.
Brian graduated magna cum laude from Duke University in 1993 and was awarded a Fulbright scholarship in linguistics in Ecuador in 1994.
WWW: https://www.processmaker.com
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Twitter: @processmaker
How do AI and other trends impact the way organizations manage and run their processes?
The fundamental shift for 2026 is the realization that Agentic AI is the natural evolution of Case Management. For decades, Case Management was the “exception” to the rule—the way we handled unstructured work that required human judgment. Now, the AI Agent has become the ultimate knowledge worker.
- From Deterministic to Intent-Driven: We are moving away from “Hard-coded Workflows.” Instead of a rigid path, we give an Agent a goal (the “Case”) and the boundaries (the “Governance”). The Agent then orchestrates the steps to reach that goal.
- The Orchestration Stack: We are seeing a “Layered Intelligence” approach. Organizations no longer rely on a single LLM. They use BPMN as the control plane to prevent “agent-to-agent” chaos (the digital equivalent of Chinese phone tag), DMN for cost-effective deterministic logic, and Agents to handle the “messy” middle of the work.
- The Death of the Static Interface: We are seeing the “disappearing UI.” Instead of users clicking through 10 screens in a portal, they are interacting with processes via natural language or voice. The process is becoming invisible, running in the background and only “surfacing” to a human when a judgment call is required.
- Process Intelligence as the Foundation: You cannot have effective AI without Process Intelligence (PI). Organizations are realizing that feeding an LLM their data isn’t enough; they need to feed it their operational context. PI acts as the digital twin that tells the AI exactly how work currently happens so the AI can actually improve it rather than just automate a broken step.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
The BPM practitioner of 2026 is less of a “Map Maker” and more of a “System Architect of Intent.”
- Skill: Governing Autonomy: You must learn how to design “BPMN Guardrails.” The skill is no longer just drawing a line from A to B; it’s defining the sandbox in which an AI Agent can safely operate without creating a feedback loop or a compliance nightmare.
- Technique: Hybrid Modeling (BPMN + DMN + LLM): Value is created by knowing which tool to use for which task. You use DMN for regulated, binary decisions to keep costs low and outcomes certain; you use BPMN to maintain the state machine; and you use Agents for everything that requires “understanding.”
- Attitude: Pragmatic Optimism: You must embrace the power of Agents to solve the “un-automatable,” but maintain a healthy skepticism regarding the “black box.” The best practitioners will be those who refuse to let agents manage agents without a structured BPMN “supervisor.”
- Skill: Prompt Engineering & AI Literacy: You don’t need to be a data scientist, but you must understand how to “instruct” an AI agent. Understanding RAG (Retrieval-Augmented Generation) and how to give an agent the right “knowledge base” is more important than knowing how to drag-and-drop a gateway.
- Technique: Value-Based Orchestration: Stop measuring “time to complete a task.” Start measuring “value created per process cycle.” In 2026, practitioners must focus on orchestrating diverse “workers”—humans, bots, and AI agents—into a unified stream.
- Attitude: Radical Agility: The business environment is too volatile for “annual process reviews.” Practitioners must adopt a mindset of continuous, real-time optimization.
What are the best resources to learn those skills? (e.g. books, articles, courses)
- The “Trifecta” Frameworks: Study the intersection of BPMN 2.0, DMN 1.x, and AI Agentic Frameworks (like LangChain or AutoGPT). Understanding how these three standards talk to each other is the “Gold Standard” of 2026.
- Case Management Theory: Revisit the core principles of CMMN (Case Management Model and Notation). Even if the notation itself is less common, the philosophy—that work is a collection of events and data rather than a straight line—is exactly how Agentic AI operates.
- Cost-Benefit Modeling for AI: Learn to calculate the “Token Cost vs. DMN Cost.” As models get larger, the ability to offload logic to deterministic DMN tables becomes a major competitive advantage in operational efficiency.
Which skills are no longer relevant or not practically applicable yet (hype)?
- Irrelevant: Perfectionist Process Mapping. If you are spending months on a “Current State” map, you are documenting the past. In 2026, Process Intelligence (PI) tells us the current state in real-time; the practitioner’s job is to design the “Governed Future State.”
- Hype: The “Agent-Only” Enterprise. There is a lot of hype around letting Agents run the whole show. This is a recipe for disaster. Without a BPMN State Machine, you lose auditability and control. We don’t want “Chinese Phone Tag” where one agent misunderstands another until the process drifts into a hallucination.
- Hype: Purely Generative Decisioning. Using an LLM to decide on a credit limit or a medical diagnosis is still a “hype” risk. For those outcomes, we still require the DMN layer for total transparency and 100% repeatability.
- Irrelevant: Manual Coding for Connectors. Building “hand-coded” integrations and scripts is a dying art. AI can now generate these connectors or use “action-based” APIs on the fly. If you are spending weeks writing integration code, you are falling behind.
- Irrelevant: Rigid BPMN Perfectionism. Spending three months perfecting a 50-page BPMN manual is now a liability. By the time you finish the map, the business environment has changed.
- Hype: Fully “Autonomous” Enterprises. While we talk a lot about agents, the idea that a company can run entirely without human oversight in 2026 is still hype. The “Human-in-the-loop” is not an elective; it is a requirement for governance, ethics, and complex decision-making.
Adrian Reed
Adrian Reed is a true advocate of the analysis profession. In his day job, he acts as Principal Consultant at Blackmetric Business Solutions where he provides business analysis consultancy and training solutions to a range of clients in varying industries. He is editor-in-chief of the quarterly open-access magazine BA Digest, and he speaks internationally on topics relating to business analysis and business change. Adrian wrote the 2016 book ‘Be a Great Problem Solver… Now’ and the 2018 book ‘Business Analyst’
You can read Adrian’s blog at http://www.adrianreed.co.uk and connect with him on LinkedIn at https://www.linkedin.com/in/adrianreed/
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How do AI and other trends impact the BA?
This is a really interesting question, Zbigniew, and one that lots of people are asking. I suppose at this point it’s worth highlighting that my background is business analysis, rather than business process management. Of course, there’s overlap, but I’m likely to have a slightly different lens on these questions compared with your other interviewees…
In my mind, this question has three core angles:
Angle 1: How can BAs utilize AI to become even more efficient and effective
Angle 2: How can BAs work with their stakeholders to ensure organizations deploy AI in an effective, ethical, safe and secure way.
Angle 3: How might customers, suppliers or “service users” start using AI, and how might that impact our processes, services or “systems” (in the broadest sense).I think a lot of the debate is currently around Angle 1, and that’s understandable. Yet, for me, Angle 2 is even more crucial. And there’s so much value that a BA can add here. One of the key ways I believe I’ve added value in my career is encouraging people to pause, stop and understand the real set of problems they are trying to solve, or outcomes they are trying to achieve. Too often, people reach for the most seductive, shiniest, newest thing. That’s human nature, we all do it. But with something like AI, where the consequences of getting it wrong could be huge, ensuring adequate thought is crucial.
Angle 3 is a big topic on its own, so that’s a blog for another time. But imagine a world where a customer sends an AI agent to interact with your company’s live chat. Do you allow that? Do you care? Can you even detect it…? But that’s just scratching the surface…
So, in my view, BAs absolutely need to be thinking about AI, experimenting, and learning.
What are the skills, techniques, behaviors, and attitudes that can help Business Analysts create value for their organizations in 2026?
For me it’s always about ensuring that the desired outcomes are stated and agreed. I’ve been on too many projects where there’s surface level agreement on what’s being delivered… but when you pick away at the edges you realize that people have no shared agreement on “why”.
This sounds trivial, but it isn’t. This can happen at a micro or macro level. People might say “we want a new CRM system” or even something like “we just want a new field”. Well fine, a new field sounds small doesn’t it?
But when you probe, you find that they want a “source of business” field so the marketing team can test which marketing campaigns work. Their actual aim is to “optimise marketing spend”. Once you know that, you can work with them to figure out a way of doing that… and spoiler alert: a new field (on its own) almost certainly won’t achieve that.
Add AI into the mix, and the potential impacts on process, policy and ethics and there needs to be someone asking the tricky questions. For example “what groups might be negatively impacted if we do this? And are we OK with that, ethically? Can we mitigate it?”, and sometimes, frankly “should we actually be doing this at all?”.
What are the best resources to learn those skills? (e.g. books, articles, courses)
Well, obviously everyone should read bpmtips.com! And I’d also plug a quarterly magazine that I edit, BA Digest. It’s completely free and available at BAdigest.link.
I’d also say find people on LinkedIn who are knowledgeable practitioners and follow them. There are too many people here that I really respect for me to name anyone (as I fear I’d leave someone out!).
Also, with AI, I genuinely think things are moving so quickly the best way to learn it is to do it. Start, experiment. If your company doesn’t currently have an AI policy, do it at home. There are so many resources out there, many are free.
Which skills are no longer relevant or not practically applicable yet (hype)?
I always struggle with this question! I find myself taking meeting notes much less frequently now, as I find usually (for non-confidential meetings) people are happy for them to be recorded and transcribed. However, I’m always very diligent about checking the meeting summaries (again, this is an area where bias can inadvertently happen. E.g. if someone is speaking English with an accent, their points may not be transcribed accurately, which means their views are not accurately represented. It’s so important to be aware of stuff like that).
But, on the whole, I think it’s “the same but different”. Business analysis has always been, in my view, a primarily human endeavour. Perhaps it’s even more so now, as AI tools can help with some of the more routine aspects, we can spend more time with people. And that has to be a good thing.
Björn Richerzhagen
The trained businessman, business economist and business IT specialist is one of the most sought-after BPM experts. The BPM rationalist has been at the interface between departments and technology for two decades now and sees himself as a translator between the worlds. As a BPM consultant and trainer, he is OCEB and CBPP certified and accompanies process initiatives at company level as well as process automation projects as a workflow analyst.
In his private life, the family man is involved in numerous community / charity projects, enjoys traveling (Europe and Africa), listens to a lot of music (everything that has bass) and is an enthusiastic ocean sailor.
WWW: https://www.mi-nautics.com/
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How do AI and other trends impact the way organizations manage and run their processes?
We observe that our customers are highly interested in AI with a strong focus on AI being a resource in a process, not so much being the resource orchestrating the process. Often they fail to identify use cases that ofter a true business benefit. Hence, it is often a discovery and get accustomed to the AI tech stacks. Anyway, we assume use cases creating a real business value are on the rise and will gain traction in 2026.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
Besides from foundational process management skills (they never get old), we foresee that proper training on AI and skills on creating effective guardrails will become most relevant things to work on. To accept AI agents will become team members will speed up process execution generally as they can be engaged in tedious work whereas human colleagues may focus on what the can do best: human oriented work, system design, creative work, exception handling etc.
What are the best resources to learn those skills? (e.g. books, articles, courses)
Numerous sources for AI and process management can be found not only in books but also on the internet. The first one is still rapidly developing. Hence, the time it takes to publicize cannot keep up with current developments. Numerous blogs, video and pod casts (mainly from scientists, vendors and consultants) offer valuable insights but have to be critically judged if it is just buzz or if it contains generally applicable principles. The latter, process management, is more profound and magazines and books can be helpful for first steps in process management. Anyway, recent developments in BPM can also be found in numerous online sources.
Which skills are no longer relevant or not practically applicable yet (hype)?
Process Mining and RPA seem to be beyond its peak. Customers invested heavily but either did not get the expected return or are now facing the consequences they have not been able to foresee. Whilst edge cases exist where a positive business value is existent, the advertised approach by tool vendors to be generally applicable on a bread range in processes turned out to be technically true but often of little value when a ROI is calculated.
Pedro Robledo
Pedro Robledo is President and Co-founder of the Spanish chapter of ABPMP International and a leading authority in Business Process Management (BPM), digital transformation, and artificial intelligence. He is the author of the Business Process Maturity Model (BPMM, 2014), a framework adopted globally to assess and elevate process maturity across seven pillars: Strategy, Processes, Technology, People, Governance, Methodologies, and Culture, helping organizations define and execute successful BPM roadmaps.
With over 25 years of experience, Pedro’s mission is to help professionals and organizations rethink, redesign, and future-proof their processes, connecting operational excellence with strategic innovation. He has led initiatives in multinational organizations and served as a jury member for the WfMC Awards for Excellence in BPM & Workflow, reinforcing his position as a recognized thought leader in the field.
Currently, Pedro focuses on:
Acting as a thought leader and architect in BPM, AI, and Autonomous Agents Designing strategic roadmaps for BPM, AI-driven automation, and enterprise architecture Researching Agentic AI and its impact on organizational process maturity Teaching and delivering advanced, strategic BPM education, bridging innovation, governance, and operational excellence
He shares insights and thought leadership through his newsletters and publications:
Diario de un COO – High-level operational management insights: https://lnkd.in/dnYn4ybU BPM & AI-Driven Innovation – The process revolution in the age of AI: https://lnkd.in/dE8eH3VR Voces BPM – Inspirational cases and people: https://www.linkedin.com/newsletters/voces-bpm-casos-testimonios-7346543494393466881/
Pedro is committed to empowering professionals and organizations to think critically about processes, moving beyond tools and certifications through consulting, advisory, frameworks, training, and applied intellectual leadership.
Philosophy: He believes that processes are not just tasks to manage—they are the foundation for innovation, resilience, and value creation in the age of AI.
Pedro’s specialties include BPM, BPMM, PEMM, AI applied to processes, Agentic AI, process innovation, enterprise architecture, process benchmarking, strategic roadmaps, BPMN, and DMN.
He currently counts 32,722 LinkedIn followers, reflecting his growing influence as a BPM and AI thought leader, with over 1,700 new followers gained in the past year.
WWW: pedrorobledobpm.blogspot.com.es
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How do AI and other trends impact the way organizations manage and run their processes?
By 2026, processes are no longer simply managed. They are co-managed with AI, but this does not mean chaos, nor does it mean abandoning structured processes.
AI has pushed BPM beyond documentation and isolated optimization toward continuous, autonomous orchestration. However, one of the biggest challenges organizations face today is not the lack of automation, but the lack of coherence. Many companies have accumulated hundreds of task-level automations, copilots, bots, and agents that optimize locally but damage performance end to end.
This is where BPM becomes more important than ever.
Processes are evolving from static representations into living operational systems. BPMN models are no longer frozen diagrams; they are increasingly connected to execution engines, process mining, and decision services, forming operational digital twins that reflect reality in near real time. These twins allow organizations to understand how work truly flows from start to finish, not just how individual tasks are automated.
At the same time, decision automation becomes a structural element. DMN is essential to ensure that AI-driven decisions remain consistent, explainable, auditable, and aligned with strategy and regulation. Without DMN, AI quickly becomes a black box operating at task level, increasing risk rather than reducing it.
This brings us to CMMN and case management, which play a crucial, but often misunderstood role. The rise of AI agents and knowledge-intensive work has revived interest in CMMN, as many business scenarios are event-driven, non-linear, and unpredictable. Case management is extremely powerful for handling variability, exceptions, and human judgment.
However, a dangerous misconception is emerging: the idea that everything should become case management.
Structured, repeatable, high-volume processes do not disappear in 2026. They still require BPMN, clear flows, performance control, and optimization. Treating all work as cases creates fragmentation, weak governance, and loss of end-to-end visibility. Autonomous agents should not live only inside CMMN worlds; they must operate across BPMN, DMN, and CMMN, depending on the nature of the work.
The real shift is not BPMN versus CMMN, but intentional orchestration. BPM provides the backbone that connects structured flows, unstructured cases, and AI-driven decisions into a coherent operating model.
Human roles, therefore, move upward. People stop managing task execution and start governing behavior, intent, and outcomes. AI handles coordination, optimization, and execution, but BPM ensures that all of this happens end to end, not in isolated pockets.
In short, BPM in 2026 becomes the discipline that prevents intelligent automation from becoming intelligent chaos. In 2026, BPM is not about choosing between BPMN, CMMN, or AI agents. It is about orchestrating them coherently. Without BPM, intelligent automation becomes fragmented, risky, and opaque. With BPM, organizations gain control, clarity, and scalability, even in an autonomous world. The real challenge is not automating more. It is automating with intent, structure, and governance. And that is exactly where BPM proves its relevance again.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
The BPM professional of 2026 is not a simple process analyst, nor a task automator. They are a business process architect and business orchestration designer.
A critical skill is the ability to design end-to-end processes that combine BPMN, DMN, and CMMN intentionally. Practitioners must know when to use structured flows, when to enable case-driven behavior, and how decisions and AI agents operate consistently across both. This architectural thinking is what separates scalable automation from fragile experimentation.
AI-first process design is no longer optional, but it must be process-first, not task-first. BPM professionals must be able to challenge initiatives that automate individual tasks without understanding upstream and downstream impact. Value in 2026 comes from optimizing the whole system, not local efficiency.
Decision-centric BPM remains essential. DMN provides the guardrails that allow autonomous agents to act responsibly across both structured processes and cases. Without decision models, agents become unpredictable and governance collapses.
Process mining skills also evolve. Practitioners must use mining not just to discover flows, but to expose fragmentation caused by disconnected automations, identifying where task-level optimization has broken end-to-end performance.
From a behavioral standpoint, BPM professionals must be comfortable saying no. No to automation without process context. No to agent deployments without governance. No to replacing structured processes with cases simply because “AI is flexible.”
Ethics and accountability remain central. As automation becomes more autonomous, BPM practitioners increasingly act as custodians of fairness, transparency, traceability, and compliance, across flows, cases, and decisions.
Above all, BPM in 2026 requires a relentless focus on business outcomes. Automating tasks is easy. Designing resilient, compliant, and scalable operating models is hard, and that is where BPM creates value.
What are the best resources to learn those skills? (e.g. books, articles, courses)
To operate at this level in 2026, learning must go far beyond tools.
The BPM classics remain essential because they teach systems thinking. Hammer, Rummler & Brache, and Weske provide the intellectual discipline needed to reason end to end, something desperately needed in an era of fragmented automation.
At the same time, practitioners must deepen their knowledge of BPMN, DMN, and CMMN as a coherent triad, not as isolated standards. Understanding how these standards complement each other is fundamental to governing AI-driven operations.
Formal education in Strategic Process Management becomes increasingly relevant, particularly when it incorporates process architecture, decision governance, AI, and maturity assessment. In complex organizations, knowing what to automate is less important than knowing what the organization is ready to automate.
This is why BPM maturity models regain strategic importance. My BPMM evolved for 2026, explicitly addressing AI, decision automation, agentic behavior, governance, and the balance between structured processes and cases, is essential to avoid both under-automation and reckless over-automation.
Beyond formal learning, practitioners must stay close to real implementations. Process mining academies, decision automation communities, and practitioner forums that discuss BPM + AI honestly (not just vendor marketing) are critical.
And, as always, experimentation matters. Working hands-on with AI agents inside structured processes and cases is the only way to truly understand where each approach adds value.
Which skills are no longer relevant or not practically applicable yet (hype)?
Some trends need to be challenged openly.
Task-level automation without end-to-end process thinking is rapidly becoming a liability. Organizations full of disconnected bots and copilots often perform worse than those with fewer but well-orchestrated automations.
Over-reliance on case management for everything is another emerging risk. CMMN is powerful, but it is not a universal replacement for BPMN. Treating all work as cases leads to loss of predictability, weak KPIs, and governance gaps.
Manual documentation and static modeling are also declining. AI now generates documentation automatically from execution data. The valuable skill is not writing documents, but validating, governing, and improving AI-generated process knowledge.
On the hype side, the idea of a fully self-managing organization remains fiction. Autonomous agents still need human-defined intent, constraints, and accountability. AGI- or ASI-driven BPM is not a practical reality in 2026, and pretending otherwise creates unrealistic expectations and poor decisions.
Prof. Michael Rosemann
Dr Michael Rosemann is the Director of the Centre for Future Enterprise and a Professor for Information Systems at the Business School, Queensland University of Technology (QUT), Brisbane, Australia.
Dr Rosemann’s main areas of research are corporate innovation, revenue resilience, process management and trust management. His work is focused on creating compelling future worlds with today’s possibilities that make current practices obsolete. As a researcher and advisor to board rooms and senior executives he is committed to advancing research-informed knowledge and confidence in order to appreciate the emerging design space and to create an increased ‘sense of ambition’ and innovation appetite.
Dr Rosemann is the author/editor of ten books, more than 350 refereed papers in outlets such as MIS Quarterly, European Journal of Information Systems, Journal of Strategic Information Systems, Information Systems and Journal of the Association of Information Systems, Editorial Board member of ten international journals (incl. MISQ Executive) and co-inventor of US and European patents. His ‘Handbook of Business Process Management’ (with Prof. Jan vom Brocke, second edition) is a comprehensive consolidation of global BPM thought leaders. His publications have been translated into German, Russian, Portuguese and Mandarin. His latest book, ‘The New Learning Economy’ (with Martin Betts), has been published by Routledge in December 2022.
Michael provides advice related to performance, innovation, trust and process management to organisations and their executives from diverse industries including telco, banking, insurance, utility, retail, public sector, higher education, logistics and the film industry. He is also the Honorary Consul of the Federal Republic of Germany in Southern Queensland.
WWW: https://www.qut.edu.au/research/michael-rosemann
WWW: http://www.michaelrosemann.com/
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How do AI and other trends impact the way organizations manage and run their processes?
AI in all its forms – machine learning, generative AI, agentic AI – has three main impacts within business processes.
First, its deep machine learning capacity provides the opportunity to delegate a new range of typical human activities to technology. This is what I call autonomization as it reflects the ability of AI to autonomously make decisions. Instead of specifying what needs to be done (automation), and as common in business process modelling, autonomization requires a definition of the why of an activity or a process. Thus, organisations need to become more explicit in terms of process objectives and related constraints and guardrails. Also, responsibility will have to complement feasibility, viability and desirability as a key criterion in assessing process improvement proposals. This is why we developed a Process Canvas consisting of these four dimensions as a way to support comprehensive process contextualisation ‘on a page’.
Second, this increased potential for delegation will make substantial capabilities exclusive to humans available for future business processes. This impact is called humanization, and a BPM community traditionally focused on streamlining processes seems poorly prepared to benefit from this capability. This is a tremendous opportunity for process designers, but it will not be adequately harvested with common reductionist, technology-centric approaches. Instead, organisations are encouraged to follow a resource-based, human-centric view and explore the extent to which personal 1-1 advice, diagnostics, therapy, care or new services can add value to its business processes. In a world of ubiquitous AI utilization, humanization might become the distinct factor in tomorrow’s business processes.
Third, augmentation describes the AI-enabled creation of entirely new forms of value resulting from the interplay of humans and machines. For example, a retailer might enhance its online shopping process by providing a conversational as opposed to a transactional experience. A bank might use proactive banking and not only anticipate but flip the process and actually run transactions on behalf of its customers. And a university might consider precision education, i.e. personalised educational processes. This emergence of new value is in sharp contrast to the common elimination of non-value.
Beyond considering the impact of AI within processes, we need to be aware of the growing role of AI on business processes. This includes the use of AI along all stages of the business process lifecycle and includes AI-supported identification of high priority processes, detection of process issues, and conversational navigation across large process data derived via process mining. In addition, we also see an increased use and maturity of AI in the context of explorative BPM, i.e. supporting BPM professionals in identifying entirely new process design options.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
With the growing AI footprint in business processes, it is needless to state that data and algorithmic literacy, but also ethical literacy will be essential.
As we witness increasingly digitised, friction-free processes, we are moving from a focus on pain points to a concentration on opportunity points within business processes. Rather than only looking to the inside and analysing existing problems, BPM practitioners also need to explore a growing process design space and assess new value opportunities. This will mean experimentation might become more important than expertise, and the social licence to experiment with corporate but also with public business processes will be required. For example, we might see (autonomous) A/B testing more often embedded in processes that otherwise were aimed for predictability and stability. The required new skills, techniques and attitude include curiosity, environmental scanning, hypothesis testing and comfort with minimum viable business processes among others.
We also encourage organizations to develop futures literacy, i.e. assess different types of process futures – preferred, plausible, possible, probable futures – and develop robust response strategies so that process designs remain decisive and agile.
What are the best resources to learn those skills? (e.g. books, articles, courses)
The global uptake of the book ‘Fundamentals of Business Process Management’ by my dear colleagues Marlon Dumas, Marcello La Rosa, Jan Mendling and Hajo Reijers demonstrates that it remains the point of reference for every BPM professional. The very recent book Enterprise AI (edited by Shazia Sadiq, published by Springer 2026) provides a contemporary overview about the impact of scalable AI capability on organisational assets including its business processes. In this book, we also elaborate on the notion of process autonomization.
There are many high-quality BPM learning resources available, often with strong regional roots. One example is the largest Brazilian BPM YouTube channel, hosted by Andréa Magalhães from dheka, who visited us here at QUT in Brisbane last year. The channel covers a broad range of BPM topics (from fundamentals to innovation, research, and emerging topics) and has an impressive 30,000+ followers. A good podcast with a strong AI lens on all matters BPM is Lukas Egger’s Process Transformers.
The International BPM Conference will take place in Toronto, Canada, end of September. This remains the event that brings the global BPM community together like no other, including various forums and workshops to specific BPM topics, and it is always a wonderful week to experience and discuss the emerging state-of-the-art.
Finally, it is great to see the uptake of the new journal Process Science, the new flagship journal on BPM and process mining.
Which skills are no longer relevant or not practically applicable yet (hype)?
As processes start to reach the state of being streamlined and digitised, techniques dedicated to the search of waste (Lean Management) and non-value might become less relevant. This will be amplified by the fact that in a world of cloud-based business processes, types of waste like bottlenecks will be a dying species.
There might be two nuanced versions of BPM becoming relevant soon. Individual Process Management (IPM) will be dedicated to the optimisation of our very own personal processes (e.g., shopping, banking, healthcare) as AI assistants might take over more of the transactional duties in our lives. As a consequence we might become orchestrators of such individual processes. How we approach and best support Individual Process Management is still in its infancy.
Public Process Management (PPM) is about entire national business processes. Digital infrastructure including government processes are becoming a new distinct competitive feature of global investment and trade attraction. The design and management of such processes is still poorly understood, exposed to a wide range of contextual factors (e.g., national risk aversion, digital literacy). The diversity of global process practices is a rich source of insight for academics and PPM professionals.
Serge Schiltz
Serge Schiltz is CEO and founder of processCentric GmbH, a European consulting and training firm focused on business process management. With his extensive practical experience as a senior consultant working with clients on their BPM challenges in different industries, he has been able to build a solid reputation over the past decades. Author, trainer, university lecturer and conference speaker in English, German and French. Member of OMG’s DMN Task Force and contributor to the OMG Certified Expert in BPM (OCEB) examination.
WWW: https://www.processcentric.ch/en
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How do AI and other trends impact the way organizations manage and run their processes?
The way that we approach process discovery could potentially take an entirely new perspective if we use generative AI tools for documenting business processes. To date, the way business representatives describe their processes is influenced by the process analyst, who typically takes a BPM expert approach and gives direction to the interviews. If we manage to build AI tools that can transform process descriptions as made by SMEs in the form of written text, audio, or video (Why not describe your processes using Lego or Playmobil for Business?), there will be less of the expert bias in process modeling and models will be truly owned by the business.
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
It remains key for BPM practitioners to understand the value proposition and strategy of the organizations that they work with. To me, OMG’s Business Motivation Model (BMM) is one of the most important tool to understand and apply for being able deliver value to an organization through BPM.
What are the best resources to learn those skills? (e.g. books, articles, courses)
The BPM certifications of OMG (OCEB certification program) cover the Business Motivation Model and it is no surprise that many candidates have difficulty answering the BMM questions. OMG’s BPM certification task force is currently finalizing the questions for the new edition of the Fundamental level exam, of which 10% will about the BMM, 70% BPMN, 15% DMN, and 5% CMMN. There is little use modeling business processes, rules, or cases, as long as you don’t understand the business context and purpose. If you are looking to understand BMM, you can read my books for the Fundamental or Intermediate exam certification preparation, or the Fundamental prep book of Tim Weilkiens. My colleague Joshua Ara and I are currently putting the final touches to a new book that will prepare you for the next edition OCEB Fundamental exam … expect this to be published late February or early March.
Which skills are no longer relevant or not practically applicable yet (hype)?
I see a lot of potential in case modeling using CMMN. Yes, this approach has not been successful (yet) and some vendors even completely scrapped if from their offering, while enhancing the capabilities of BPMN adhoc subprocesses. I expect that this proprietary approach will disappear in the near future and that BPM practioners will at last understand the value that the standard CMMN brings. Read Bruce Silver’s “CMMN Method & Style” if you are not familiar with it yet, or my new book that I mentioned above. There are excellent tools on the market that offer CMMN support. Watch out for Trisotech and Flowable!
Jim Sinur
Jim Sinur is an independent thought leader in applying smart Digital Business Platforms (DBP), Customer Experience/Journeys (CJM), Business Process Management (BPM), AI, Automation (RPA), Low-code and Decision Management at the edge for enhanced business outcomes. His research and areas of personal experience focus on intelligent business processes, business modeling, real time data feedback with heterogeneous data types, business process management technologies, smart process collaboration for knowledge workers, process intelligence/optimization, AI applied to business policy/rule management, IoT and leveraging business applications in processes. Jim was a contributor to Forbes in AI. Jim is also one of the authors of BPM: The Next Wave. His latest book is Digital Transformation. Innovate or Die Slowly. Jim also co-authored recently a new book entitled “Practical Business Process Modeling and Analysis”. Jim’s personal blog is approaching two million hits to date. Jim is also a well known digital and traditional artist. His recent adventures include songwriting. He is revisualizing his art and marketing his music with generative AI.
WWW: https://www.forbes.com/sites/cognitiveworld/people/jimsinur/
WWW: http://www.james-sinur.com/
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What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
There are a number of skills that BPM folks could pick up as there are many in the middle of digital evolution assisted by AI, but my top seven would be the following:
- Journey Mapping for Customers, Employees and Partners including touchpoint analysis and persona creation that crosses internal functional stovepipes. Outside-in Thinking.
- Embedded Advanced Analytic and Visualization Capabilities. Process plus big, fast and dark process/data mining is growing to be more important. Decision Models and Intelligent Management Cockpits will become more important as they integrate with process models. Strategic and situational analysis can be helpful in guiding agents and processes.
- Agentic AI, Adaptive, Smart and Goal Driven Processes (often in Case Management and also Explicit Rule enabled) guided by guardrails and by process/data mining with real time feedback. Concentrating on Agents inside and outside a process or process snippets. Snippets and RPA bots are often candidates for converting into agents. Get ready for specialty agents such as broker agents.
- AI Productivity Focused looking for opportunities to add automation or more smarts like Generative AI. Machine learning, Deep Learning and 17 other AI technology tributaries. See the 20 AI tributaries by clicking here: https://jimsinur.blogspot.com/2023/11/ai-tributaries-types-for-2024.htm
- Cognitive Collaboration for Knowledge Workers Intense Processes or Cases. AI Assistance for process resources is on the move right now. Leveraging learning AI software and Agents for knowledge building and simulating potential outcomes. Having Skills to interact and guide AI in an interactive fashion will be key.
- Signal and Pattern Detection at the edge (often needed for agility, IoT and business strategy). IoT integration is a new emerging theme. This can be taken to the level of digital twins and by merging control on the edge with central control.
- Business Professional Process creation, adaptation, and optimization by leveraging lite BPM/workflow, Process/Data Mining utilizing Low code and generative AI.
Which skills are no longer relevant or not practically applicable yet (hype)?
While there are no skills that one should drop, there are several that are considered common and receding. My top three would be the following:
- Central Control Only approaches with siloed skill sets. More lateral thinking is and collaborative control is needed today.
- Water Fall Only project methods are taking a second seat to incremental development leveraging Generative AI, RPA and rapid experimentation. We are living in an emergent world with emergent responses required.
- Large blocks of dumb frozen code are giving way to smart and instrumented components, micro services and late binding rules guided by constraints. Turn dumb code into adaptive agents where possible.
Roger Tregear
Roger Tregear spends his working life talking, consulting, thinking, presenting, recording, and writing about the analysis, innovation, improvement, and management of business processes. He helps organizations improve performance.
As Principal Advisor at TregearBPM Roger provides business process management consulting, training, and coaching services. 36 years’ experience as a business, management, and IT consultant means that he has well-developed insights into business improvement and problem resolution.
Roger’s practice and client base are global with assignments completed in Australia, Bahrain, Belgium, Jordan, Namibia, Nigeria, Netherlands, Saudi Arabia, South Africa, South Korea, Switzerland, New Zealand, United Arab Emirates, UK, and USA.
Roger writes, presents, and records on many topics related to process-based management. That material can be accessed via https://bit.ly/TregearBPM_Resources.
WWW: https://www.tregearbpm.com
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Twitter: @rogertregear
What advice would you give organization leaders who want to start managing processes intentionally in 2026?
Do This:
- Identify the organization’s processes in a hierarchical format (process architecture). This is not hard to do and has two important effects. Provides a coherent context for understanding the organization’s processes. Promotes understanding of the key principles of process-based management.
- Select a small number of high-impact processes and use these to establish and demonstrate active process management. For many organizations there will be 20-30 high-impact processes. You might start by selecting just three demonstration processes.
- Design and implement effective process governance. Assign Process Owners (PO) to the demonstration processes. Establish support arrangements for these new POs. Clearly communicate the need for, and practice of, process governance.
- For the demonstration processes identify process KPIs (PKPIs) and related targets. Make sure there are viable data collection mechanisms.
- Establish the data collection, analysis, and reporting cycle. Look for actual or emerging problems. Search for other opportunities for performance improvement. Repeat endlessly.
- Create and execute a whole-of-organization communications plan to share the theory and practice of active process management. Communicate the plans, successes, and failures. Deal with fears, uncertainties, and doubts throughout the organization.
- Deliver proven, valued, business benefits. Encourage engagement.
- Prepare to survive success, i.e. dealing with (many) more business units asking for active process management support and guidance.
- Regularly review the process of process management and improvement. Make it the organization’s most effective process. Imagine the impact of that!
- Plan to appear in BPM Tips next year as an exceptional example of active process management!
Don’t Do This:
- Don’t just focus on the processes that self-select by being broken or difficult. They may be important but are they the processes that can provide the highest return?
- Don’t try to manage “all your processes”. You can’t do it — there are thousands of them — and the good news is you don’t need to.
- If starting the process-based management journey, avoid the temptation to start with lots of processes to actively manage. Better to demonstrate success with 3 than failure with 30.
- Process documentation is important but challenge the business/operational purpose before any documentation effort is started. What’s the problem the documentation will fix? Avoid the insanity of “we will model all our processes”. Document just in time, not just in case.
- Don’t underestimate the degree of change involved in moving to process-based management. Cross-functional management is vital and can be challenging for some people and organizations.
- Don’t take the ‘easy’ path and ‘assign’ existing functional KPIs to processes. Put the functional KPIs aside and design effective process KPIs (PKPIs) and targets (and measurement methods).
- Don’t allow the organization to fall in love with the process artifacts it creates and waste time admiring them at the expense of using them to deliver proven, valued, business benefits. Realize innovative and productive opportunities. Fix — better yet, anticipate and avoid — real problems.
- Don’t give up.
Roland Woldt
Roland Woldt is a well-rounded executive with 25+ years of Business Transformation consulting and software development/system implementation experience, in addition to leadership positions within the German Armed Forces (11 years).
He has worked as a Team Lead, Engagement/Program Manager, and Enterprise/Solution Architect on many projects. Within these projects, he was responsible for the full project life-cycle, from shaping a solution and selling it, to setting up a methodological approach through design, implementation, and testing, up to the roll-out of solutions.
In addition to this, Roland has managed consulting offerings throughout their life-cycle, from definition, delivery to update, and had revenue responsibility for them. This also included the stand-up and development of consulting teams, and their day-to-day management. Roland worked as a Vice President at iGrafx, Director in KPMG’s Advisory, as a Practice Director at Software AG/IDS Scheer, and as a project manager at Accenture.
WWW: “What’s Your Baseline?” podcast
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How do AI and other trends impact the way organizations manage and run their processes?
The topic of AI is cooling down a bit these days, it seems (good, because it is overhyped to the degree that I roll my eyes when I see the next “AI expert” telling me that everything is changing on LinkedIn. I just hope that the bubble will not explode (to a degree that makes the dot.com or housing bubble look tiny comparatively), but rather that there will be a controlled release of hot air.
Let’s call things what they are – AI is a form of process automation. Nothing more, nothing less.
Yes, it has some advanced capabilities, like learning from previous process executions, or having more autonomy in orchestrating things in a workflow, but it is still “just automation” and not your “new coworker” or any other anthropomorphic nonsense (“If it looks like a duck, quacks like a duck, …”).
So, with that out of the way, I see a few things that are relevant for BPM practitioners in regards to AI:
- There will be more AI features in every software and vendors will stress this until it becomes “normal” and is not a distinguishing feature anymore. This will be true for process management software as well (I am including the subdiscipline of mining here) , but the quality for the foreseeable future will be the one of “little helpers.”
If you expect to see a full blown analysis or simulation on the press of a button (or prompt), then you will be disappointed.- AI will have a bigger impact when it comes to automation. Here I see the biggest potential in orchestration and executing the “dummy tasks” that cost a lot of time today. Do I think that you can “fire and forget” processes and replace what you do today (and the humans involved included)? No, and I am not sorry to disappoint you.
- But this also means that you need to get the basics of process management right – understand and optimize processes before automation, creating simulations for business cases, describe your intended changes in solution designs, and monitor the process execution, while keeping the risk & compliance topics always in mind.
I would love to see process groups mature into these higher-levels of maturity, but it seems that we are still discussing how to describe what we do, instead of aiming for CMMI 4 or 5 levels of maturity (note to everyone in the former camp: BPMN won, don’t try to reinvent the wheel, go and improve things higher in the stack).So, things change and stay the same as they’ve always been
What are the skills, techniques, behaviors, and attitudes that can help BPM practitioners create value for their organizations in 2026?
I hope that 2026 will be the year when data-driven analysis will finally take off. Gartner rated Process Mining as “early mainstream” in their Enterprise Automation hype cycle earlier this year, which means that it is in the 20-50% addressable audience for this approach … and this means these are people who have never heard about mining at all, so don’t confuse them with “object-centric mining” or any other terms that are “hot” in our bubble these days. Stick to the basics.
I find it astonishing how many organizations still “fly blind” when running their organizations and don’t measure or even just monitor what they are doing. Process Mining is becoming an affordable commodity where you don’t have to pay an arm and a leg to get process-oriented visibility into what is really going on in your organization – and not only what your SMEs know or want to tell you.
If I could dream even more, I would love to see more collaboration (not only of SMEs in mining projects, which you will need for sure), but also in the full process lifecycle that then will include things like a central repository, strategic analysis of capabilities and finding improvement areas systematically, or process simulation.
And, of course, I would love to see more collaboration between the practitioners in real life. It seems that there are some great initiatives of Meetups in Germany for example, but I have not found anything similar in my neck of the woods, unfortunately.
What are the best resources to learn those skills? (e.g. books, articles, courses)
I am biased because I published two books -Successful Architecture Implementation and Successful Process Mining Projects- last year. And I run the “What’s Your Baseline”?” podcast together with [email protected] and the occasional co-hosts (thanks [email protected] and [email protected] so far) for 4.5 years by now. And there is more to come in 2026 (IYKYK
If you want to learn more, please head over to whatsyourbaseline.com.
But in general I think it is important to learn data analysis skills as a BA. And the one tool that I really like is KNIME (knime.com) – it allows you to create workflows for data analysis or preparation of process mining logs without the need for coding in a “self documenting” way. And the folks in that community are super helpful (in the forums) and also have free-of-charge training for different roles on the website.
And did I mention that it is open-source? The perfect tool IMHO.Lastly, there are also some basics to be learned, and if you are brand new here and want to know what that whole process thing is all about and how you can describe them, I recommend Zbigniew’s BPMN course on Udemy of course
Which skills are no longer relevant or not practically applicable yet (hype)?
The post BPM Skills in 2026 – Hot or Not first appeared on BPM Tips.I mentioned it above, but I think that data analysis in the context of mining and simulation will become more relevant, and there will be some improvements on the technology front as well. My hunch is that by the end of the year the majority of tool vendors will have enabled object-centric data sets in their tools, so you will have to change how you do step 3 of my approach to Process Mining. This will come with some challenges and complexities (not at least based on the fact that your data structure and governance in your organization might be a mess) that you will have to overcome.
But otherwise I think the fundamentals of describing your processes, analyzing them, automating processes, predicting future performance, and monitoring the realization of everything does not change. Why should it?
